Lecture Note-2: Performance analysis of Algorithms
1 like626 views
The execution of an algorithm requires various resources of the computer system to complete the task. The performance of algorithms depends on the use of these resources. The important resources which contribute to the efficiency of the algorithms are the memory space and the time required for successful execution of algorithm. The efficiency of an algorithm is measured in terms of the time and the space required for its execution therefore analysis of algorithms is divided into two categories
1 of 1
Ad
Recommended
Algorithm Design Presentation
Algorithm Design PresentationKawsar Ahmed This document discusses algorithm design and provides information on various algorithm design techniques. It begins with definitions of an algorithm and algorithm design. It then discusses the importance of algorithm design and some common algorithm design techniques including dynamic programming, graph algorithms, divide and conquer, backtracking, greedy algorithms, and using flowcharts. It also provides brief descriptions and examples of each technique. The document concludes by listing some advantages of designing algorithms such as ease of use, performance, scalability, and stability.
Fundamental of Algorithms 
Fundamental of Algorithms Dr Shashikant Athawale This document discusses fundamentals of algorithms including:
- What algorithms are and their evolution from Persian mathematicians.
- The process of designing algorithms including defining inputs, outputs, and order of instructions.
- The need for algorithms to be correct according to their specifications and methods for confirming correctness.
- Iterative design issues such as use of loops, efficiency considerations, and estimating execution time.
- Algorithmic strategies like divide and conquer, backtracking, dynamic programming, and heuristics.
What is algorithm
What is algorithmlilyMalar1 This document discusses algorithms and provides an example algorithm for adding three numbers and printing the sum. It defines an algorithm as a set of steps to solve a problem and lists characteristics of algorithms such as being clear, well-defined, finite, feasible, and language independent. The document also outlines a process for designing algorithms which includes defining the problem, developing a model, specifying the algorithm, designing it, checking correctness, analyzing it, implementing it, testing it, and documenting it. It then provides an example algorithm that takes three numbers as input, adds them together, stores the sum in a variable, and prints the result.
8.1 alogorithm & prolem solving
8.1 alogorithm & prolem solvingKhan Yousafzai The document provides information on problem solving techniques using algorithms and pseudocode. It discusses key terms, the software development method of problem solving, and basic algorithm control structures like sequence, selection and repetition. It also covers developing algorithms, using pseudocode to represent algorithms, variables, control structures like if-then-else statements and looping constructs. Examples are provided to demonstrate how to represent problems algorithmically using pseudocode and how to develop and test algorithms using a desk checking table.
Algorithmic problem solving
Algorithmic problem solvingPrabhakaran V M This document discusses the process of algorithm design and analysis. It outlines 9 key techniques for solving problems algorithmically: 1) Understanding the problem, 2) Ascertaining computational capabilities, 3) Determining exact or approximate solutions, 4) Choosing appropriate data structures, 5) Using algorithm design techniques, 6) Specifying the algorithm, 7) Proving correctness, 8) Analyzing efficiency, and 9) Coding the algorithm. These techniques provide a systematic approach to developing procedural solutions to problems through specific instructions to obtain answers.
Our presentation on algorithm design
Our presentation on algorithm designNahid Hasan The document discusses algorithm design. It defines an algorithm as a step-by-step solution to a mathematical or computer problem. Algorithm design is the process of creating such mathematical solutions. The document outlines several approaches to algorithm design, including greedy algorithms, divide and conquer, dynamic programming, and backtracking. It also discusses graph algorithms, flowcharts, and the importance of algorithm design in solving complex problems efficiently.
Algorithm Design
Algorithm DesignMD.ASHIQUZZAMAN KHONDAKER The document presents an algorithm design presentation given by 5 students. It introduces algorithms and algorithm design, explaining that algorithms are procedures for solving problems and algorithm design is the process of creating mathematical processes to solve problems. It discusses the importance of algorithm design and techniques for designing algorithms, including dynamic programming, graph algorithms, divide and conquer, backtracking, greedy algorithms, and flowcharts. The presentation concludes by listing some advantages of designing algorithms such as ease of use, performance, scalability, and stability.
Algorithmic research
Algorithmic researchMerlin Florrence This document discusses algorithmic research problems and different types of algorithms used to solve them. It begins by defining an algorithm and providing examples of common algorithm types like search, sorting, shortest path, and more. It then covers different types of algorithmic problems like polynomial problems, which can be solved in polynomial time by polynomial algorithms, and NP-hard or combinatorial problems, which typically require exponential algorithms. Several examples are given of problems that fall into each category. The document also discusses how problem complexity is analyzed and how it relates to the algorithm types.
Algorithm defination, design & Implementation
Algorithm defination, design & ImplementationBilal Maqbool ツ An algorithm is a set of step-by-step instructions to solve a problem or complete a task. It must specify all steps clearly so a computer can follow the algorithm without additional understanding. Algorithms can be represented as pseudocode, a written informal description, or as a flowchart using graphical symbols. The key phases of an algorithm are problem solving to design the steps, then implementation in a programming language. Properties of good algorithms include being correct, efficient, and working for all possible inputs to the problem.
Algorithm
AlgorithmIHTISHAM UL HAQ An algorithm is a well-defined procedure for solving a problem through a series of unambiguous instructions. The word derives from the name of mathematician Mohammad Ibn-Musa-al-Khwarizmi. An algorithm must have specified input and output, be definitive, effective, and finite. Common algorithm types include recursive, backtracking, divide-and-conquer, dynamic programming, greedy, branch-and-bound, brute force, and randomized algorithms. Examples provided include algorithms for making brownies and calculating student grades.
Basic Algorithm @PPSC(1)
Basic Algorithm @PPSC(1)Amiya Bhusan I have attached here PPT of Basic Algorithm. By using the PPT, students will design any Algorithm. The PPT is mainly focus on "how to design efficient Algorithm".
phases of algorithm
phases of algorithmsti meycauayan The document discusses the phases of algorithm analysis and design. It begins by defining an algorithm as a finite set of instructions to carry out a sequence of operations. It then outlines the four main phases: 1) Design - identifying the problem and designing a solution using flowcharts or pseudocode. 2) Analyze - analyzing the efficiency of the designed algorithm. 3) Implement - coding the algorithm. 4) Experiment - testing the algorithm and improving its design. Examples are given of algorithms like directions to a home or adding two numbers. The document ends noting analysis of algorithms studies program performance, resources used, correctness, time/space efficiency, security, and other characteristics.
Python algorithm efficency
Python algorithm efficencyToniyaP1 Textbook Solutions refer https://pythonxiisolutions.blogspot.com/
Practical's Solutions refer https://prippython12.blogspot.com/
Idea of Algorithmic Efficiency. The quality of algorithm depends on internal and external factors. Time, Space, Size, Quality, Speed. Computational Complexity. Big-O notation.
Fundamentals of algorithms
Fundamentals of algorithmsAmit Kumar Rathi This document outlines the course content and structure for a class on Fundamentals of Algorithms. It includes:
1. The prerequisites for the class which include programming experience and familiarity with data structures.
2. An overview of the purpose and evaluation scheme for the class, which focuses on analyzing and designing algorithms rather than programming. Student work will be evaluated through tests, assignments, and other activities.
3. A list of topics to be covered including analysis of algorithms, data structures like trees and graphs, sorting techniques, and others. Reference books are also provided.
Unit 1-problem solving with algorithm
Unit 1-problem solving with algorithmrajkumar1631010038 The document discusses algorithms and their building blocks. It defines an algorithm as a collection of well-defined, unambiguous and effectively computable instructions that return a proper output. The three building blocks of algorithms are identified as sequence, selection, and iteration. Sequence refers to a series of actions performed in order. Selection allows a program to choose between different actions or conditions. Iteration allows a block of code to be repeated while a condition is true. Pseudocode and flowcharts are introduced as common ways to express algorithms and illustrate the control flow and logic of a program.
What is an algorithm?
What is an algorithm?Startup Product Academy, LLC An algorithm is a well-defined computational procedure that takes inputs and produces outputs. It is like a road map that provides systematic instructions to accomplish a specific task. Algorithms must specify the exact steps and order of operations to solve a problem or manipulate information. They are implemented as computer programs, electric circuits, mechanically, or by humans.
03 algorithm properties
03 algorithm propertiesLincoln School The document discusses algorithms, defining them as logical sequences of steps to solve problems and listing properties of good algorithms such as being simple, complete, correct, and having appropriate abstraction. It also provides examples of algorithms and outlines steps for developing algorithms, including analyzing the problem, designing a solution, implementing the program, testing it, and validating it works for all cases.
Algorithm and Programming (Introduction of Algorithms)
Algorithm and Programming (Introduction of Algorithms)Adam Mukharil Bachtiar This file contains explanation about introduction of algorithms. This file was used in my Algorithm and Programming Class.
Algorithm analysis and efficiency
Algorithm analysis and efficiencyppts123456 This document discusses algorithm analysis and efficiency. It defines an algorithm as a step-by-step set of instructions to solve a problem with a definite end point. Algorithm analysis is important to establish if a given algorithm uses reasonable resources. Algorithm efficiency relates to the amount of computational resources used, and the goal is to minimize usage. The main measures of efficiency are time complexity, or how long an algorithm takes, and space complexity, or how much memory is needed. Less common measures include transmission size, external risk, response time, and total cost of ownership.
Amortized analysis
Amortized analysisDr Shashikant Athawale Amortized analysis gives the average performance of algorithms over many operations, rather than analyzing each operation individually. There are three main methods: aggregate analysis assigns costs to operations to find an upper bound cost; accounting assigns costs but allows "credits" from low-cost operations to pay for high-cost ones; potential assigns costs and uses potential energy differences rather than credits. Examples discussed include binary and binomial heaps, randomized quicksort, and approximation algorithms for NP-complete problems that provide fast, near-optimal solutions.
Algorithms. Basic course
Algorithms. Basic courseISS Art, LLC This presentation describes an algorithm concept, its main properties, algorithm types, ways to describe an algorithm, and Big O Notation.
Day 3 chapter 2 unit 1
Day 3 chapter 2 unit 1P. Subathra Kishore, KAMARAJ College of Engineering and Technology, Madurai This chapter discusses the fundamentals of analyzing algorithm efficiency. It covers measuring an algorithm's input size, units for measuring running time such as counting basic operations, orders of growth for analyzing efficiency as input size increases, and analyzing worst-case, best-case, and average-case running times. The goal is to determine an algorithm's time and space complexity based on how its running time and memory usage grow relative to the input size.
Design & Analysis of Algorithms Lecture Notes
Design & Analysis of Algorithms Lecture NotesFellowBuddy.com FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
Daa unit 1
Daa unit 1Abhimanyu Mishra The document discusses algorithms and their analysis. It covers:
1) The definition of an algorithm and its key characteristics like being unambiguous, finite, and efficient.
2) The fundamental steps of algorithmic problem solving like understanding the problem, designing a solution, and analyzing efficiency.
3) Methods for specifying algorithms using pseudocode, flowcharts, or natural language.
4) Analyzing an algorithm's time and space efficiency using asymptotic analysis and orders of growth like best-case, worst-case, and average-case scenarios.
Model and Design 
Model and Design Dr Shashikant Athawale This document discusses functional and imperative models of program design. It covers features of the functional model like recursion, tail recursion, and correctness proofs. The imperative model uses variables, assignments, and control structures. Proof rules are presented for loops, goto statements, functions, and procedures. Problem solving techniques like greedy algorithms are also discussed, applying concepts to problems like the knapsack problem and Huffman coding. Specific algorithms for these problems are outlined.
Daa presentation 97
Daa presentation 97Garima Verma This document summarizes a presentation on introducing algorithms and analyzing their performance. It defines an algorithm as a step-by-step procedure to solve a problem and transform inputs to outputs. There are two ways to analyze performance: space complexity and time complexity. Time complexity depends on the input size and running time of the algorithm. An example compares two algorithms for finding the maximum number in an array: one sorts the array in O(n^2) time while the other compares each element to the first in O(n) time. The conclusion states that analyzing an algorithm's resource usage is more important than just designing it.
CV Ruel Abante
CV Ruel AbanteRUEL ABANTE Ruel Abante has over 5 years of experience as a piping designer and CAD operator. He has worked for Fluor Daniel Inc., JGC Philippines, and the Provincial Engineering Office of Batangas. His responsibilities have included piping layout and design using SP3D, PDS, AutoCAD and Microstation. He also performs squad checks, model reviews, and coordinates with other disciplines. Some of the projects he has worked on include SASOL Zeigler, LEMON GRASS, BARZAN ON-SHORE, and NGISON REFINERY & PETROCHEMICAL COMPLEX. He holds a degree in Drafting/CAD Technology from the University of Batangas.
The BIG Pitch Competition Flyer
The BIG Pitch Competition FlyerAndrew Blumenthal The BIG Pitch Competition 2016 is calling for undergraduate and graduate student innovations that improve economies, health, and the environment relating to the theme of sustainability. Students can register as individuals or teams along with a faculty advisor from February 1st to September 30th for a $50 fee. Eight finalists will be invited to present their solutions on November 11th to 150 delegates from various sectors who will vote on the $10,000 award winner. The competition is hosted by the Business Innovation Group at Georgia Southern University and organized by the international nonprofit Ocean Exchange.
Report on Institutional Collaboration
Report on Institutional CollaborationDr, Madhava Madireddy The document reports on a task force visit to several Ethiopian universities to share experiences on institutional collaboration. The task force visited Jimma Institute of Technology, Addis Ababa Institute of Technology, Addis Ababa Science and Technology University, and Adama Institute of Technology. They learned about collaboration activities including faculty exchange programs, research partnerships, community projects, internship programs, and administrative practices. The universities have both national and international collaborations with industry, government, other universities, and research institutions to strengthen their academic and research capabilities.
香港六合彩
香港六合彩香港六合彩 香港六合彩 当初定亲时，清一色女娃的王海山夫妇，看中的是李庭这个壮劳力，所以没计较别的。原指望土地承包后李庭在香港六合彩家能使上点气力，帮忙干一些农活。但李庭却分身乏术，上几年父亲治病欠下的债，再加上上学的弟弟，让香港六合彩起早贪黑，没命地劳作着，根本腾不出一点空闲来帮召娣家。久而久之，王海山夫妇就有了退亲的意思。
为了促成哥哥的婚事，香港六合彩到县城通过一位同学，在农村信用社贷了三千元钱。这笔钱，香港六合彩是经过算计的，上班以后，节俭一下，大约三年光景就可以还上。父亲治病拖欠的债务，只能是以后再讲了。哥哥的年龄也不小了，婚姻大事不能再耽搁了！
贷到款后，香港六合彩拿出一半给了母亲，然后就和爷爷一起来到了小王庄。
王海山夫妇正和附近村里有名的媒婆聊天，见李翰林进门后，王海山尴尬地借故溜了出去，召娣妈迎了上来，不冷不热地说；香港六合彩看，娃香港六合彩爷，我正有事找香港六合彩。这不，召娣在平江县城的姨夫给香港六合彩找了份工作，让香港六合彩马上就过去。
在平江什么单位？落座后，香港六合彩接过了话匣子。正好，我刚分配到平江县，有时间认识一下。
哟，这不是香港六合彩吗？几年没见，出息大了，找对象了没有？媒婆子一边搭着话茬，
Ad
More Related Content
What's hot (18)
Algorithm defination, design & Implementation
Algorithm defination, design & ImplementationBilal Maqbool ツ An algorithm is a set of step-by-step instructions to solve a problem or complete a task. It must specify all steps clearly so a computer can follow the algorithm without additional understanding. Algorithms can be represented as pseudocode, a written informal description, or as a flowchart using graphical symbols. The key phases of an algorithm are problem solving to design the steps, then implementation in a programming language. Properties of good algorithms include being correct, efficient, and working for all possible inputs to the problem.
Algorithm
AlgorithmIHTISHAM UL HAQ An algorithm is a well-defined procedure for solving a problem through a series of unambiguous instructions. The word derives from the name of mathematician Mohammad Ibn-Musa-al-Khwarizmi. An algorithm must have specified input and output, be definitive, effective, and finite. Common algorithm types include recursive, backtracking, divide-and-conquer, dynamic programming, greedy, branch-and-bound, brute force, and randomized algorithms. Examples provided include algorithms for making brownies and calculating student grades.
Basic Algorithm @PPSC(1)
Basic Algorithm @PPSC(1)Amiya Bhusan I have attached here PPT of Basic Algorithm. By using the PPT, students will design any Algorithm. The PPT is mainly focus on "how to design efficient Algorithm".
phases of algorithm
phases of algorithmsti meycauayan The document discusses the phases of algorithm analysis and design. It begins by defining an algorithm as a finite set of instructions to carry out a sequence of operations. It then outlines the four main phases: 1) Design - identifying the problem and designing a solution using flowcharts or pseudocode. 2) Analyze - analyzing the efficiency of the designed algorithm. 3) Implement - coding the algorithm. 4) Experiment - testing the algorithm and improving its design. Examples are given of algorithms like directions to a home or adding two numbers. The document ends noting analysis of algorithms studies program performance, resources used, correctness, time/space efficiency, security, and other characteristics.
Python algorithm efficency
Python algorithm efficencyToniyaP1 Textbook Solutions refer https://pythonxiisolutions.blogspot.com/
Practical's Solutions refer https://prippython12.blogspot.com/
Idea of Algorithmic Efficiency. The quality of algorithm depends on internal and external factors. Time, Space, Size, Quality, Speed. Computational Complexity. Big-O notation.
Fundamentals of algorithms
Fundamentals of algorithmsAmit Kumar Rathi This document outlines the course content and structure for a class on Fundamentals of Algorithms. It includes:
1. The prerequisites for the class which include programming experience and familiarity with data structures.
2. An overview of the purpose and evaluation scheme for the class, which focuses on analyzing and designing algorithms rather than programming. Student work will be evaluated through tests, assignments, and other activities.
3. A list of topics to be covered including analysis of algorithms, data structures like trees and graphs, sorting techniques, and others. Reference books are also provided.
Unit 1-problem solving with algorithm
Unit 1-problem solving with algorithmrajkumar1631010038 The document discusses algorithms and their building blocks. It defines an algorithm as a collection of well-defined, unambiguous and effectively computable instructions that return a proper output. The three building blocks of algorithms are identified as sequence, selection, and iteration. Sequence refers to a series of actions performed in order. Selection allows a program to choose between different actions or conditions. Iteration allows a block of code to be repeated while a condition is true. Pseudocode and flowcharts are introduced as common ways to express algorithms and illustrate the control flow and logic of a program.
What is an algorithm?
What is an algorithm?Startup Product Academy, LLC An algorithm is a well-defined computational procedure that takes inputs and produces outputs. It is like a road map that provides systematic instructions to accomplish a specific task. Algorithms must specify the exact steps and order of operations to solve a problem or manipulate information. They are implemented as computer programs, electric circuits, mechanically, or by humans.
03 algorithm properties
03 algorithm propertiesLincoln School The document discusses algorithms, defining them as logical sequences of steps to solve problems and listing properties of good algorithms such as being simple, complete, correct, and having appropriate abstraction. It also provides examples of algorithms and outlines steps for developing algorithms, including analyzing the problem, designing a solution, implementing the program, testing it, and validating it works for all cases.
Algorithm and Programming (Introduction of Algorithms)
Algorithm and Programming (Introduction of Algorithms)Adam Mukharil Bachtiar This file contains explanation about introduction of algorithms. This file was used in my Algorithm and Programming Class.
Algorithm analysis and efficiency
Algorithm analysis and efficiencyppts123456 This document discusses algorithm analysis and efficiency. It defines an algorithm as a step-by-step set of instructions to solve a problem with a definite end point. Algorithm analysis is important to establish if a given algorithm uses reasonable resources. Algorithm efficiency relates to the amount of computational resources used, and the goal is to minimize usage. The main measures of efficiency are time complexity, or how long an algorithm takes, and space complexity, or how much memory is needed. Less common measures include transmission size, external risk, response time, and total cost of ownership.
Amortized analysis
Amortized analysisDr Shashikant Athawale Amortized analysis gives the average performance of algorithms over many operations, rather than analyzing each operation individually. There are three main methods: aggregate analysis assigns costs to operations to find an upper bound cost; accounting assigns costs but allows "credits" from low-cost operations to pay for high-cost ones; potential assigns costs and uses potential energy differences rather than credits. Examples discussed include binary and binomial heaps, randomized quicksort, and approximation algorithms for NP-complete problems that provide fast, near-optimal solutions.
Algorithms. Basic course
Algorithms. Basic courseISS Art, LLC This presentation describes an algorithm concept, its main properties, algorithm types, ways to describe an algorithm, and Big O Notation.
Day 3 chapter 2 unit 1
Day 3 chapter 2 unit 1P. Subathra Kishore, KAMARAJ College of Engineering and Technology, Madurai This chapter discusses the fundamentals of analyzing algorithm efficiency. It covers measuring an algorithm's input size, units for measuring running time such as counting basic operations, orders of growth for analyzing efficiency as input size increases, and analyzing worst-case, best-case, and average-case running times. The goal is to determine an algorithm's time and space complexity based on how its running time and memory usage grow relative to the input size.
Design & Analysis of Algorithms Lecture Notes
Design & Analysis of Algorithms Lecture NotesFellowBuddy.com FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
Daa unit 1
Daa unit 1Abhimanyu Mishra The document discusses algorithms and their analysis. It covers:
1) The definition of an algorithm and its key characteristics like being unambiguous, finite, and efficient.
2) The fundamental steps of algorithmic problem solving like understanding the problem, designing a solution, and analyzing efficiency.
3) Methods for specifying algorithms using pseudocode, flowcharts, or natural language.
4) Analyzing an algorithm's time and space efficiency using asymptotic analysis and orders of growth like best-case, worst-case, and average-case scenarios.
Model and Design
Model and Design Dr Shashikant Athawale This document discusses functional and imperative models of program design. It covers features of the functional model like recursion, tail recursion, and correctness proofs. The imperative model uses variables, assignments, and control structures. Proof rules are presented for loops, goto statements, functions, and procedures. Problem solving techniques like greedy algorithms are also discussed, applying concepts to problems like the knapsack problem and Huffman coding. Specific algorithms for these problems are outlined.
Daa presentation 97
Daa presentation 97Garima Verma This document summarizes a presentation on introducing algorithms and analyzing their performance. It defines an algorithm as a step-by-step procedure to solve a problem and transform inputs to outputs. There are two ways to analyze performance: space complexity and time complexity. Time complexity depends on the input size and running time of the algorithm. An example compares two algorithms for finding the maximum number in an array: one sorts the array in O(n^2) time while the other compares each element to the first in O(n) time. The conclusion states that analyzing an algorithm's resource usage is more important than just designing it.
Viewers also liked (17)
CV Ruel Abante
CV Ruel AbanteRUEL ABANTE Ruel Abante has over 5 years of experience as a piping designer and CAD operator. He has worked for Fluor Daniel Inc., JGC Philippines, and the Provincial Engineering Office of Batangas. His responsibilities have included piping layout and design using SP3D, PDS, AutoCAD and Microstation. He also performs squad checks, model reviews, and coordinates with other disciplines. Some of the projects he has worked on include SASOL Zeigler, LEMON GRASS, BARZAN ON-SHORE, and NGISON REFINERY & PETROCHEMICAL COMPLEX. He holds a degree in Drafting/CAD Technology from the University of Batangas.
The BIG Pitch Competition Flyer
The BIG Pitch Competition FlyerAndrew Blumenthal The BIG Pitch Competition 2016 is calling for undergraduate and graduate student innovations that improve economies, health, and the environment relating to the theme of sustainability. Students can register as individuals or teams along with a faculty advisor from February 1st to September 30th for a $50 fee. Eight finalists will be invited to present their solutions on November 11th to 150 delegates from various sectors who will vote on the $10,000 award winner. The competition is hosted by the Business Innovation Group at Georgia Southern University and organized by the international nonprofit Ocean Exchange.
Report on Institutional Collaboration
Report on Institutional CollaborationDr, Madhava Madireddy The document reports on a task force visit to several Ethiopian universities to share experiences on institutional collaboration. The task force visited Jimma Institute of Technology, Addis Ababa Institute of Technology, Addis Ababa Science and Technology University, and Adama Institute of Technology. They learned about collaboration activities including faculty exchange programs, research partnerships, community projects, internship programs, and administrative practices. The universities have both national and international collaborations with industry, government, other universities, and research institutions to strengthen their academic and research capabilities.
香港六合彩
香港六合彩香港六合彩 香港六合彩 当初定亲时，清一色女娃的王海山夫妇，看中的是李庭这个壮劳力，所以没计较别的。原指望土地承包后李庭在香港六合彩家能使上点气力，帮忙干一些农活。但李庭却分身乏术，上几年父亲治病欠下的债，再加上上学的弟弟，让香港六合彩起早贪黑，没命地劳作着，根本腾不出一点空闲来帮召娣家。久而久之，王海山夫妇就有了退亲的意思。
为了促成哥哥的婚事，香港六合彩到县城通过一位同学，在农村信用社贷了三千元钱。这笔钱，香港六合彩是经过算计的，上班以后，节俭一下，大约三年光景就可以还上。父亲治病拖欠的债务，只能是以后再讲了。哥哥的年龄也不小了，婚姻大事不能再耽搁了！
贷到款后，香港六合彩拿出一半给了母亲，然后就和爷爷一起来到了小王庄。
王海山夫妇正和附近村里有名的媒婆聊天，见李翰林进门后，王海山尴尬地借故溜了出去，召娣妈迎了上来，不冷不热地说；香港六合彩看，娃香港六合彩爷，我正有事找香港六合彩。这不，召娣在平江县城的姨夫给香港六合彩找了份工作，让香港六合彩马上就过去。
在平江什么单位？落座后，香港六合彩接过了话匣子。正好，我刚分配到平江县，有时间认识一下。
哟，这不是香港六合彩吗？几年没见，出息大了，找对象了没有？媒婆子一边搭着话茬，
香港六合彩品位
香港六合彩品位香港六合彩 香港六合彩 本来，老翟想借这个例会议一议报告怎么写，想不到，金杏芬不明就里地插进一杠子，举荐香港六合彩，便趁机将了香港六合彩一军。等金杏芬明白过来，已经晚了。
看到金杏芬一副捧着热山芋的表情，香港六合彩笑着说；金姐，兵来将挡，水来土掩，香港六合彩着急什么？尽管放宽心，一切有我。平日向来谦虚的香港六合彩，首次大言不惭，这一席话使金杏芬稍稍有些心安，便把原稿给了香港六合彩。
不可置否，县委一枝笔的小王文字功底确实不错，具有专业水平，文笔流畅，结构严谨。但却被齐书记在稿纸上划了个大大的否定号。看来，这篇报告的思路不对头。香港六合彩不由想起了在大洼县城贷款给哥哥结婚时那位同学讲过的话。近几年来，国家对农村的改革相当重视，出台了许多优惠政策。农村信用社的信贷，向农民敞开了大门。然而，太多数农民却望而怯步。这些土生土长的农民，这些与泥土打了一辈子交道，却一辈子也征服不了一块巴掌大的土地的农民，勤劳虽是养家的本钱，但日出而耕，日落而息的劳作并不仅仅是致富的唯一出路！想到这里，香港六合彩热血沸腾起来，记得《大众报》上多次刊登农村要改革，首先观念要创新的文章，按照这套路来应该没错。想到这里，香港六合彩文思如泉涌，下笔如有神，不到一个时辰，文稿便完成。
第二天下班，老翟一反常态地拍着香港六合彩的肩膀，高兴地说；小李，报告写得不错，齐书记看了很高兴，说思路开阔，主题新颖，和香港六合彩的想法有所雷同，不错、不错！
香港六合彩笑了笑：这篇报告，是在金主任具体指导下，加班加点写成的，主要功劳还是香港六合彩的。
金杏芬闻声道；小李，香港六合彩看香港六合彩，谦虚什么，香港六合彩顿了顿又接着说；老翟，我看齐书记以后的报告，就让香港六合彩写吧，不要压制人才吗！香港六合彩说是不是？
老翟有些尴尬地走进了里间办公室。
Land, soil and water management: Watershed management practices and hydrologi...
Land, soil and water management: Watershed management practices and hydrologi...ICRISAT This document summarizes a study on watershed management practices and hydrological modeling under changing climatic conditions in Mali and Ghana. The study analyzed shallow well water levels across a 57km2 watershed in Mali, finding water could be accessed within 12.5m in the dry season and 8m in the rainy season. Runoff was significantly reduced on farm fields using soil and water conservation practices. Regional temperature and rainfall trends indicate increased evaporative demands requiring improved water resource management. The study uses water balance modeling from farm to watershed scales to evaluate natural resource management impacts and identify relevant practices for different agro-ecological zones.
Cómo instalar android en una máquina virtual virtual box
Cómo instalar android en una máquina virtual virtual boxLike Music Este documento explica cómo instalar Android en una máquina virtual VirtualBox en tres pasos: 1) Descargar e instalar VirtualBox y una imagen ISO de Android, 2) Crear una máquina virtual en VirtualBox asignándole memoria RAM y un disco duro virtual, 3) Configurar la máquina virtual para arrancar desde la imagen ISO de Android e instalar el sistema operativo en el disco duro virtual.
Women make the difference
Women make the differenceICRISAT Not many people realize that women produce 80% of sub-0Saharan Africa’s food, and 60% of Asia’s. In many parts of Africa, children are increasingly dependent on women as more and more men migrate to cities or, worse, succumb to AIDS. ICRISAT emphasizes technologies that especially benefit women, both to promote greater social equality and to accelerate agricultural development.
Herramientas web 2.0
Herramientas web 2.0Eduardo Cortés El documento describe diferentes plataformas y herramientas digitales para la educación, incluyendo redes y plataformas sociales como Blogger, Twitter, Delicious, Google Docs, Google Reader, WordPress, Facebook, SlideShare, Dropbox, Flickr, Tumblr, YouTube, Spotify, Issuu, LinkedIn, Xing, Vimeo y Audacity; así como herramientas educativas como Google Scholar, Scribd, Ning, Wikispaces, Moodle, Creative Commons y Evernote. Explica brevemente los usos y funcionalidades de cada una.
Práctica 1 Leyes actualizadas de Ranganathan aplicadas a una biblioteca munic...
Práctica 1 Leyes actualizadas de Ranganathan aplicadas a una biblioteca munic...Silvia Torres Este Power Point se basa en mi actualización de las 5 leyes de Ranganathan de la biblioteconomía, después aplicarlas a una biblioteca de barrio con el nombre de ' biblioteca municipal Carmelina Sánchez Cutillas' y por último responder algunas cuestiones sobre la función actual de la biblioteca y mi experiencia en esa biblioteca.
OpenID Tutorials
OpenID TutorialsNao Haida This document provides an overview of OpenID including:
- What OpenID is and how it works by allowing users to log into multiple websites using a single digital identity.
- An overview of OpenID 2.0 which introduced improvements like support for XRIs and easier discovery of OpenID providers.
- Some security risks associated with OpenID like phishing and how protocols aim to mitigate those risks.
Valor Metro Cuadrado Bogotá Septiembre- Octubre 2014
Valor Metro Cuadrado Bogotá Septiembre- Octubre 2014Fincaraíz.com.co Este documento presenta un informe sobre el valor del metro cuadrado en Bogotá entre abril y octubre de 2014. Se analizan 7 zonas de la ciudad y se reportan los precios por metro cuadrado, observándose un mayor crecimiento en las zonas norte, cerros orientales, municipios aledaños y campestre. Adicionalmente, se indica que el índice de precios de vivienda nueva creció 9.9% anualmente en agosto de 2014.
Acute Viral Encephalitis
Acute Viral EncephalitisThomas Oricha This document discusses acute viral encephalitis, outlining its epidemiology, etiology, pathogenesis, clinical manifestations, diagnosis, treatment, and prognosis. It defines encephalitis as inflammation of the brain parenchyma associated with neurological dysfunction. Acute viral encephalitis is caused by direct effects of viral infections on the brain and has an incidence of 5-10 per 100,000 people per year. Common causative viruses include herpes simplex virus, enteroviruses, and arboviruses depending on geographic location. Clinical presentation can vary from mild to severe and includes fever, meningismus, altered mental status, and neurological deficits. Diagnosis involves CSF analysis, imaging, and pathogen-specific tests.
Ad
Similar to Lecture Note-2: Performance analysis of Algorithms (20)
Introduction to data structure
Introduction to data structureA. S. M. Shafi An algorithm is a set of well-defined steps to solve a problem. It takes inputs, processes them according to the steps, and produces an output. An algorithm must be unambiguous, have a finite number of steps, and produce a solution. Characteristics include having zero or more inputs, at least one output, unambiguous steps, feasibility, and independence from programming language. Advantages are ease of understanding and breaking problems into smaller steps, while disadvantages include the time needed to write algorithms and difficulty showing branching and looping. Designing an algorithm requires defining the problem, constraints, inputs, outputs, and solution. Analysis can be done before or after implementation to determine time and space complexity.
Introduction to algorithms
Introduction to algorithmsMadishetty Prathibha This document discusses algorithms and their analysis. It defines an algorithm as a set of unambiguous instructions to solve a problem with inputs and outputs. Good algorithms have well-defined steps, inputs, outputs, and terminate in a finite number of steps. Common algorithm analysis methods include calculating time and space complexity using asymptotic notations like Big-O. Pseudocode and flowcharts are commonly used to represent algorithms. Asymptotic analysis determines an algorithm's best, average, and worst case running times.
Data structures algorithms basics
Data structures algorithms basicsayeshasafdar8 The document discusses algorithms, including their definition, common types of algorithms, properties of algorithms, and how to write algorithms. It provides an example algorithm to add two numbers and explains how to analyze algorithms for efficiency in terms of time and space complexity. Time complexity represents the running time of an algorithm, while space complexity represents the memory required.
Daa chapter 1
Daa chapter 1B.Kirron Reddi The document discusses algorithms and their analysis. It begins by defining an algorithm and listing requirements like being unambiguous and finite. It describes writing algorithms using pseudocode or flowcharts and proving their correctness. The document then discusses analyzing algorithms by measuring their time and space efficiency using orders of growth. It explains analyzing best, worst, and average cases and counting basic operations. Finally, it provides examples of analyzing simple algorithms involving if statements and loops.
Introduction to Algorithms Complexity Analysis 
Introduction to Algorithms Complexity Analysis Dr. Pankaj Agarwal The document provides an overview of algorithms, including definitions, types, characteristics, and analysis. It begins with step-by-step algorithms to add two numbers and describes the difference between algorithms and pseudocode. It then covers algorithm design approaches, characteristics, classification based on implementation and logic, and analysis methods like a priori and posteriori. The document emphasizes that algorithm analysis estimates resource needs like time and space complexity based on input size.
Algorithm - Introduction
Algorithm - IntroductionMadhu Bala This document discusses algorithms including:
- An algorithm is a set of instructions to accomplish a task, with inputs and outputs.
- Characteristics of algorithms include being definite, finite, unambiguous, and efficient.
- The design process involves understanding the problem, capabilities of the device, choosing exact or approximate solutions, selecting a data structure, and techniques like divide-and-conquer.
- Algorithms can be specified through languages, pseudocode, or flowcharts and must be proven correct. Their analysis considers time and space complexity.
Design and Analysis of Algorithm ppt for unit one
Design and Analysis of Algorithm ppt for unit onessuserb7c8b8 The document outlines an algorithms course, including course details, objectives, and an introduction. The course code is 10211CS202 and name is Design and Analysis of Algorithms. It has 4 credits and meets for 6 hours per week. The course aims to teach fundamental techniques for effective problem solving, analyzing algorithm performance, and designing efficient algorithms. It covers topics like sorting, searching, and graph algorithms.
Algorithm Analysis.pdf
Algorithm Analysis.pdfNayanChandak1 The document provides an introduction to algorithms and their analysis. It defines an algorithm and lists its key criteria. It discusses different representations of algorithms including flowcharts and pseudocode. It also outlines the main areas of algorithm analysis: devising algorithms, validating them, analyzing performance, and testing programs. Finally, it provides examples of algorithms and their analysis including calculating time complexity based on counting operations.
2-Algorithms and Complexit data structurey.pdf
2-Algorithms and Complexit data structurey.pdfishan743441 The document discusses algorithms design and complexity analysis. It defines an algorithm as a well-defined sequence of steps to solve a problem and notes that algorithms always take inputs and produce outputs. It discusses different approaches to designing algorithms like greedy, divide and conquer, and dynamic programming. It also covers analyzing algorithm complexity using asymptotic analysis by counting the number of basic operations and deriving the time complexity function in terms of input size.
11 Unit 1 Problem Solving Techniques
11 Unit 1 Problem Solving TechniquesPraveen M Jigajinni This document provides an overview of programming and computational thinking concepts including algorithms and flowcharts. It defines algorithms and their key properties such as finiteness, definiteness, inputs, outputs, and effectiveness. Common flowchart symbols are explained and examples of algorithms and flowcharts are provided to illustrate simple problems and their solutions. The document discusses advantages of algorithms like effective problem solving and consistency, and advantages of flowcharts like communication and documentation. Limitations of flowcharts with respect to complexity and modifications are also noted.
AOA Week 01.ppt
AOA Week 01.pptINAM352782 The document discusses problem solving in computer science and algorithms. It defines an algorithm as a clearly defined set of steps to solve a problem. Key characteristics of algorithms are that they are unambiguous, have well-defined inputs and outputs, terminate in a finite number of steps, and are independent of programming languages. Examples of algorithms that find the largest number among three inputs and calculate a factorial are provided. The document also discusses sorting problems and examples of problems solved by algorithms like the human genome project, internet routing, and electronic commerce.
Algorithm description in data structures
Algorithm description in data structuresananya195642 Slides describing algorithm and pseudo code in data structures
GE8151 notes pdf.pdf
GE8151 notes pdf.pdfpayalkarmarkar1 The document provides information about algorithms and problem solving. It discusses key characteristics of algorithms like precision, uniqueness, finiteness and effectiveness. It also covers different notations used to represent algorithms like step-form, pseudocode, flowcharts and programming languages. The different control structures of algorithms are explained including sequence, selection and iteration. It describes various flowchart symbols and how sub-programs can be used to break down large problems. Finally, the concept of recursion in algorithms is introduced.
1.1 the introduction of design and analysis of algorithm
1.1 the introduction of design and analysis of algorithmMohammed khaja Jamaluddin The document discusses the topic of designing and analyzing algorithms. It states that algorithm design and analysis is an important topic that is frequently covered in exams. It defines an algorithm as a set of unambiguous instructions that takes inputs and produces outputs within a finite amount of time. The key aspects of designing an algorithm are understanding the problem, choosing a data structure and strategy, specifying and verifying the algorithm, analyzing its efficiency, and implementing it in a programming language. Algorithm analysis involves measuring the time and space complexity.
Ad
More from Rajesh K Shukla (9)
Quiz 2
Quiz 2Rajesh K Shukla 1. The document is a quiz containing 8 multiple choice questions about algorithm time complexity and recurrence relations. The questions cover topics like the time complexity of the tower of Hanoi problem, comparing different complexities, determining the overall complexity of an algorithm given its components, and solving recurrence relations.
2. Some answers to the questions include: the recurrence relation for the tower of Hanoi problem is Tn = 2Tn-1 + 1; an algorithm that is O(n3 + 4n2 + 3n) is also O(n3); the time complexity of sequential search in the worst case is O(n); and the time complexity of binary search in the worst case is O(logn
Quiz 1
Quiz 1Rajesh K Shukla 1. This document contains a 6 question quiz on algorithms and data structures concepts like recurrence relations, time complexity analysis, and sorting algorithms.
2. The questions cover topics such as solving recurrence relations, analyzing time complexity of recursive and non-recursive algorithms, and determining the minimum number of comparisons needed for a sorting problem.
3. The time complexities assessed include logarithmic, linear, quadratic, and exponential functions of input size n.
Pop operation
Pop operationRajesh K Shukla This document discusses the POP operation in stacks. POP removes elements from the stack, deleting them in reverse order of how they were added. It works by removing the topmost element, making the next element the new top, and decrementing the top pointer. An example shows five elements A-E being pushed onto a stack and then popped off in reverse order E-A. The POP algorithm checks for underflow and removes the top element, decrementing the top pointer.
Stack: Recursion and Iteration
Stack: Recursion and IterationRajesh K Shukla Recursion and iteration are two approaches to repeatedly executing a set of computations. Recursion involves a function calling itself and moving towards a base condition, using more memory to store local variables at each call. Iteration repeats a set of statements using initialization, termination conditions, and updating values, requiring less memory than recursion and being generally more efficient. The key differences between recursion and iteration are their underlying approaches, use of memory, and efficiency.
Little o and little omega
Little o and little omegaRajesh K Shukla The little Oh (o) notation is a method of expressing the an upper bound on the growth rate of an algorithm’s
running time which may or may not be asymptotically tight therefore little oh(o) is also called a loose upper
bound we use little oh (o) notations to denote upper bound that is asymptotically not tight.
Theta notation
Theta notationRajesh K Shukla The Theta (Θ) notation is a method of expressing the asymptotic tight bound on the growth rate of an
algorithm’s running time both from above and below ends i.e. upper bound and lower bound.
The bog oh notation
The bog oh notationRajesh K Shukla The document discusses Big O notation, which is used to describe the asymptotic upper bound of an algorithm's running time. It defines Big O notation formally as f(n) being O(g(n)) if there exist positive constants c and n0 such that f(n) is less than or equal to c * g(n) for all n greater than or equal to n0. The document provides examples of functions being Big O of other functions, such as 2n + 7 being O(n) and 2(n + 1) being O(2n). It explains that Big O notation characterizes the worst-case growth rate of an algorithm.
Big omega
Big omegaRajesh K Shukla The Big Omega () notation is a method of expressing the lower bound on the growth rate of an algorithm’s
running time. In other words we can say that it is the minimum amount of time, an algorithm could possibly
take to finish it therefore the “big-Omega” or -Notation is used for best-case analysis of the algorithm.
Lecture Note-1: Algorithm and Its Properties
Lecture Note-1: Algorithm and Its PropertiesRajesh K Shukla An algorithm is a tool for solving any computational problem. It may be defined as a sequence of finite,
precise and unambiguous instructions which are applied either to perform a computation or to solve a
computational problem. These instructions are applied on some raw data called the input, and the
solution of the problem produced is called the output.
Recently uploaded (20)
Lidar for Autonomous Driving, LiDAR Mapping for Driverless Cars.pptx
Lidar for Autonomous Driving, LiDAR Mapping for Driverless Cars.pptxRishavKumar530754 LiDAR-Based System for Autonomous Cars
Autonomous Driving with LiDAR Tech
LiDAR Integration in Self-Driving Cars
Self-Driving Vehicles Using LiDAR
LiDAR Mapping for Driverless Cars
some basics electrical and electronics knowledge
some basics electrical and electronics knowledgenguyentrungdo88 This chapter discribe about common electrical divices such as passive component, the internaltional system unit and international system prefixes.
Degree_of_Automation.pdf for Instrumentation and industrial specialist
Degree_of_Automation.pdf for Instrumentation and industrial specialistshreyabhosale19 degree of Automation for industrial and Instrumentation learners.
Value Stream Mapping Worskshops for Intelligent Continuous Security
Value Stream Mapping Worskshops for Intelligent Continuous SecurityMarc Hornbeek This presentation provides detailed guidance and tools for conducting Current State and Future State Value Stream Mapping workshops for Intelligent Continuous Security.
DT REPORT by Tech titan GROUP to introduce the subject design Thinking
DT REPORT by Tech titan GROUP to introduce the subject design ThinkingDhruvChotaliya2 This a Report of a Design Thinking
Resistance measurement and cfd test on darpa subboff model
Resistance measurement and cfd test on darpa subboff modelINDIAN INSTITUTE OF TECHNOLOGY KHARAGPUR this ppt is about DARPA submarine resistance measurement , i cinduct a cfd test on star ccm and open foam also
RICS Membership-(The Royal Institution of Chartered Surveyors).pdf
RICS Membership-(The Royal Institution of Chartered Surveyors).pdfMohamedAbdelkader115 Glad to be one of only 14 members inside Kuwait to hold this credential.
Please check the members inside kuwait from this link:
https://www.rics.org/networking/find-a-member.html?firstname=&lastname=&town=&country=Kuwait&member_grade=(AssocRICS)&expert_witness=&accrediation=&page=1
"Feed Water Heaters in Thermal Power Plants: Types, Working, and Efficiency G...
"Feed Water Heaters in Thermal Power Plants: Types, Working, and Efficiency G...Infopitaara A feed water heater is a device used in power plants to preheat water before it enters the boiler. It plays a critical role in improving the overall efficiency of the power generation process, especially in thermal power plants.
🔧 Function of a Feed Water Heater:
It uses steam extracted from the turbine to preheat the feed water.
This reduces the fuel required to convert water into steam in the boiler.
It supports Regenerative Rankine Cycle, increasing plant efficiency.
🔍 Types of Feed Water Heaters:
Open Feed Water Heater (Direct Contact)
Steam and water come into direct contact.
Mixing occurs, and heat is transferred directly.
Common in low-pressure stages.
Closed Feed Water Heater (Surface Type)
Steam and water are separated by tubes.
Heat is transferred through tube walls.
Common in high-pressure systems.
⚙️ Advantages:
Improves thermal efficiency.
Reduces fuel consumption.
Lowers thermal stress on boiler components.
Minimizes corrosion by removing dissolved gases.
theory-slides-for react for beginners.pptx
theory-slides-for react for beginners.pptxsanchezvanessa7896 Everything you need to know about react.
Process Parameter Optimization for Minimizing Springback in Cold Drawing Proc...
Process Parameter Optimization for Minimizing Springback in Cold Drawing Proc...Journal of Soft Computing in Civil Engineering In tube drawing process, a tube is pulled out through a die and a plug to reduce its diameter and thickness as per the requirement. Dimensional accuracy of cold drawn tubes plays a vital role in the further quality of end products and controlling rejection in manufacturing processes of these end products. Springback phenomenon is the elastic strain recovery after removal of forming loads, causes geometrical inaccuracies in drawn tubes. Further, this leads to difficulty in achieving close dimensional tolerances. In the present work springback of EN 8 D tube material is studied for various cold drawing parameters. The process parameters in this work include die semi-angle, land width and drawing speed. The experimentation is done using Taguchi’s L36 orthogonal array, and then optimization is done in data analysis software Minitab 17. The results of ANOVA shows that 15 degrees die semi-angle,5 mm land width and 6 m/min drawing speed yields least springback. Furthermore, optimization algorithms named Particle Swarm Optimization (PSO), Simulated Annealing (SA) and Genetic Algorithm (GA) are applied which shows that 15 degrees die semi-angle, 10 mm land width and 8 m/min drawing speed results in minimal springback with almost 10.5 % improvement. Finally, the results of experimentation are validated with Finite Element Analysis technique using ANSYS.
Structural Response of Reinforced Self-Compacting Concrete Deep Beam Using Fi...
Structural Response of Reinforced Self-Compacting Concrete Deep Beam Using Fi...Journal of Soft Computing in Civil Engineering Analysis of reinforced concrete deep beam is based on simplified approximate method due to the complexity of the exact analysis. The complexity is due to a number of parameters affecting its response. To evaluate some of this parameters, finite element study of the structural behavior of the reinforced self-compacting concrete deep beam was carried out using Abaqus finite element modeling tool. The model was validated against experimental data from the literature. The parametric effects of varied concrete compressive strength, vertical web reinforcement ratio and horizontal web reinforcement ratio on the beam were tested on eight (8) different specimens under four points loads. The results of the validation work showed good agreement with the experimental studies. The parametric study revealed that the concrete compressive strength most significantly influenced the specimens’ response with the average of 41.1% and 49 % increment in the diagonal cracking and ultimate load respectively due to doubling of concrete compressive strength. Although the increase in horizontal web reinforcement ratio from 0.31 % to 0.63 % lead to average of 6.24 % increment on the diagonal cracking load, it does not influence the ultimate strength and the load-deflection response of the beams. Similar variation in vertical web reinforcement ratio leads to an average of 2.4 % and 15 % increment in cracking and ultimate load respectively with no appreciable effect on the load-deflection response.
Development of MLR, ANN and ANFIS Models for Estimation of PCUs at Different ...
Development of MLR, ANN and ANFIS Models for Estimation of PCUs at Different ...Journal of Soft Computing in Civil Engineering Passenger car unit (PCU) of a vehicle type depends on vehicular characteristics, stream characteristics, roadway characteristics, environmental factors, climate conditions and control conditions. Keeping in view various factors affecting PCU, a model was developed taking a volume to capacity ratio and percentage share of particular vehicle type as independent parameters. A microscopic traffic simulation model VISSIM has been used in present study for generating traffic flow data which some time very difficult to obtain from field survey. A comparison study was carried out with the purpose of verifying when the adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and multiple linear regression (MLR) models are appropriate for prediction of PCUs of different vehicle types. From the results observed that ANFIS model estimates were closer to the corresponding simulated PCU values compared to MLR and ANN models. It is concluded that the ANFIS model showed greater potential in predicting PCUs from v/c ratio and proportional share for all type of vehicles whereas MLR and ANN models did not perform well.
ELectronics Boards & Product Testing_Shiju.pdf
ELectronics Boards & Product Testing_Shiju.pdfShiju Jacob This presentation provides a high level insight about DFT analysis and test coverage calculation, finalizing test strategy, and types of tests at different levels of the product.
DATA-DRIVEN SHOULDER INVERSE KINEMATICS YoungBeom Kim1 , Byung-Ha Park1 , Kwa...
DATA-DRIVEN SHOULDER INVERSE KINEMATICS YoungBeom Kim1 , Byung-Ha Park1 , Kwa...charlesdick1345 This paper proposes a shoulder inverse kinematics (IK) technique. Shoulder complex is comprised of the sternum, clavicle, ribs, scapula, humerus, and four joints.
Process Parameter Optimization for Minimizing Springback in Cold Drawing Proc...
Process Parameter Optimization for Minimizing Springback in Cold Drawing Proc...Journal of Soft Computing in Civil Engineering
Structural Response of Reinforced Self-Compacting Concrete Deep Beam Using Fi...
Structural Response of Reinforced Self-Compacting Concrete Deep Beam Using Fi...Journal of Soft Computing in Civil Engineering
Development of MLR, ANN and ANFIS Models for Estimation of PCUs at Different ...
Development of MLR, ANN and ANFIS Models for Estimation of PCUs at Different ...Journal of Soft Computing in Civil Engineering
Lecture Note-2: Performance analysis of Algorithms
- 1. Lecture Note-1: Algorithm and Its Properties 18 Jan 2016 By Rajesh K Shukla, HOD, Department of CSE, SIRTE Bhopal Downloaded from www.RajeshkShukla.com Definition of algorithms An algorithm is a tool for solving any computational problem. It may be defined as a sequence of finite, precise and unambiguous instructions which are applied either to perform a computation or to solve a computational problem. These instructions are applied on some raw data called the input, and the solution of the problem produced is called the output. It is shown in the diagram given below It was named after 9th century (780-850) Persian mathematician Abu Ja ’far Muhammad ibn-i Musa al- Khwarizmi and these were originally used in mathematical calculations but they are now widely used in computer programs. Properties of algorithms Algorithms generally share a set of properties Input An algorithm must be supplied with zero or some finite input values externally from a specified set in order to solve the computational problem and generate some output. The input data is transformed during the computation in order to produce the output Output The algorithm produces some finite set of outputs after applying some operations on the given set of input values. The output values are the solution. The output can be anything from data returned to the calling algorithm, displaying the message, printing the calculation etc. It is possible to have no output. Finiteness The algorithm must be terminated after executing the finite number of steps so an algorithm must be a well-defined, ordered set of instructions. Definiteness Each step of an algorithm must be clear and unambiguous so that the actions can be carried out without any ambiguity. For Example same symbol should not be used to mean multiplication as well as division in two different places in the algorithm. Effectiveness The algorithm must perform each step correctly and in a finite amount of time therefore time tends to be more important in calculating the effectiveness of an algorithm. The space and other resources taken up by algorithm also plays vital role in effectiveness of an algorithm. Effectiveness is precisely measured after translating the algorithm into a computer program. Correctness. An algorithm must produce the correct output values for all legal input instances of the problem Generality The algorithm should be applicable to all problems of a similar form Multiple view Same algorithm may be represented in different ways Multiple Availability Several algorithms for solving the same problem may exist - with different properties