Decision 1 (AQA) 1. Introductory Ideas Algorithm = set of instructions = flowchart = program Should apply to general case and be as concise as possible. • Graph • Vertex/node (point) • Edge/arc (line) • Multiple arc • Loop Connected graph Graph where can travel from any point to any other point somehow Simple graph No multiple arcs or loops Complete graph Simple graph where every node connected to every other node by exactly one arc Network Weighted graph Degree/order of node
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2) THIVIYA NADARAJ SN089841 3) JESJEET SINGH SW089804 4) FAREESH SAILESH TIMBADIA SW090964 QUESTION 1 (a) Genetic Algorithms were invented to mimic some of the processes observed in the evolutionary ideas of genetic and natural selection based on survival of the fittest. Explain each step of the Genetic Algorithm. There are three main steps for genetic algorithm which is random initialization of population‚ evaluation of fitness function and generation of new population. In random
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Ashwin Mishra et al. / International Journal of Engineering Science and Technology (IJEST) SINGULARITY ANALYSIS AND COMPARITIVE STUDY OF SIX DEGREE OF FREEDOM STEWART PLATFORM AS A ROBOTIC ARM BY HEURISTIC ALGORITHMS AND SIMULATED ANNEALING ASHWIN MISHRA Department of Mechanical Engineering‚ Sardar Vallabhbhai National Institute of Technology‚ Surat 395007‚ Gujarat‚ India DR. S. N. OMKAR Department of Aerospace Engineering‚ Indian Institute of Science Bangalore 560012‚ Karnataka‚ India Abstract
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An analogue electronic circuits diagnosis with the use of evolutionary algorithms Piotr Jantos Damian Grzechca Jerzy Rutkowski Division of Circuits and Signals Theory Division of Circuits and Signals Theory Division of Circuits and Signals Theory Institute of Electronics Institute of Electronics Institute of Electronics Silesian University of Technology Silesian University of Technology Silesian University of Technology Gliwice‚ 44-100‚ Poland Gliwice‚ 44-100‚ Poland Gliwice‚ 44-100‚ Poland Email:
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International Journal of Computer Applications (0975 – 8887) Volume 41– No.5‚ March 2012 Data Mining Application in Enrollment Management: A Case Study Surjeet Kumar Yadav Saurabh pal Research scholar‚ Shri Venkateshwara University‚ J. P. Nagar‚ (U.P.) India Head‚ Dept. of MCA VBS Purvanchal University‚ Jaunpur‚ India ABSTRACT In the last two decades‚ number of Higher Education Institutions (HEI) grows rapidly in India. This causes a cut throat competition among these institutions
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realized and inventory leftover (shortage) is assessed. We use stochastic programming to model this problem‚ and propose an optimal bundle-type algorithm to solve it. Furthermore‚ we develop some simple and effective approximation algorithms for several special cases. Extensive numerical experiments are conducted to show the effectiveness of the approximation algorithms‚ to compare the performance between the traditional production model and the postponement production model‚ and to examine the impact of
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CHAPTER 5 CPU Scheduling Practice Exercises 5.1 A CPU-scheduling algorithm determines an order for the execution of its scheduled processes. Given n processes to be scheduled on one processor‚ how many different schedules are possible? Give a formula in terms of n. Answer: n! (n factorial = n × n – 1 × n – 2 × ... × 2 × 1). Explain the difference between preemptive and nonpreemptive scheduling. Answer: Preemptive scheduling allows a process to be interrupted in the midst of its execution
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(Buble Sort‚ Selection Sort‚ Insertion Sort) 1. ssObjectives a. Know how‚ in reality‚ three simple sorting methods work. b. Know how to use analysis tool to compare performance of sorting algorithms 2. Problem statement a. Write a Java program to measure time (in seconds) needed for each simple sorting algorithms applying on the same random array of integer values. Sizes of arrays are accordingly 10000‚ 15000‚ 20000‚ 25000‚ 30000‚ 35000‚ 40000‚ 45000 and 50000. Each time‚ you write down the measured
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avoidance is one of the main concerns of every robot’s trajectory. Planning path algorithm is the important step to avoid obstacle during the motion of autonomous robot. Many algorithms have been implemented and are being worked upon for further improvement. This report deals with some of the important algorithms used in the robot industry. Key Words – Path-planning‚ robot’s trajectory‚ obstacle avoidance‚ TSP‚ Genetic Algorithm‚ Vector Potential Field‚ Visibility Graph List of tables and Figures Symbols
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Kenya Methodist University DLM instructional material KENYA METHODIST UNIVERSITY DLM BOOKLET FAULTY : COMPUTING AND INFORMATICS DEPARTMENT : COMPUTER SCIENCE COURSE CODE COURSE NAME LECTURER CONTACT : CISY422/BBIT333 : ARTIFICIAL INTELLIGENCE : ROBERT MUTUA MURUNGI : 0710 480 450‚ r_mutua@yahoo.com 1st edition ©2012 Artificial Intelligence by Robert Mutua Murungi – I.T Lecturer 1 Kenya Methodist University DLM instructional material KENYA METHODIST UNIVERSITY P.O.
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