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miller5356: 金币+10, ★★★★★最佳答案 2016-03-30 17:54:44
sunshan4379: LS-EPI+1, 感谢应助! 2016-03-30 17:55:36
EI检索:


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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