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ÌâÄ¿:Test Points Selection Method Research Based on Genetic Algorithm and Binary Particle Swarm Optimization Algorithm. ×÷Õß:Xiaofeng Lv, Ling Ma, Jing Sun [ ·¢×ÔÊÖ»ú°æ https://muchong.com/3g ] |
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EI¼ìË÷£º Accession number: 20153201153879 Title: Test point selection method research based on genetic algorithm and binary particle swarm optimization algorithm Authors: Lv, Xiaofeng1 ; Ma, Ling1 ; Sun, Jing1 ; Pang, Wei1 Author affiliation: 1Naval Aeronautical and Astronautical University, Yantai, China Corresponding author: Lv, Xiaofeng Source title: Lecture Notes in Electrical Engineering Abbreviated source title: Lect. Notes Electr. Eng. Volume: 334 Issue date: 2015 Publication year: 2015 Pages: 577-585 Language: English ISSN: 18761100 E-ISSN: 18761119 Document type: Journal article (JA) Publisher: Springer Verlag Abstract: Test point selection is the foundation of testability analysis and design. A minimal complete subset of genetic algorithm and binary particle swarm optimization algorithm is proposed to meet testability index requirements. Firstly, the mathematical model is established based on analyzing the testability problems. Then, the heuristic function is constructed to measure the pros and cons of the test set. Experimental results show that the algorithm can effectively overcome the deficiency of a single algorithm going into a local optimum and premature convergence, and improve the searching efficiency to obtain a global optimal solution quickly. © Springer International Publishing Switzerland 2015. Number of references: 10 Main heading: Algorithms Controlled terms: Genetic algorithms - Heuristic algorithms - Optimization - Particle swarm optimization (PSO) Uncontrolled terms: Binary particle swarm optimization - Global optimal solutions - Heuristic functions - Local optima - Pre-mature convergences - Searching efficiency - Test point selection - Testability Analysis Classification code: 723 Computer Software, Data Handling and Applications - 723.1 Computer Programming - 921 Mathematics - 921.5 Optimization Techniques DOI: 10.1007/978-3-319-13707-0_63 Database: Compendex Compilation and indexing terms, © 2016 Elsevier Inc. |
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baiyuefei
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3Â¥2016-03-30 12:45:19













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