DocumentCode :
532460
Title :
Comprehensive evaluation of Automatic Test System based on neural net and cloud model
Author :
Xie, Huayong ; Xiao, Mingqing ; Yu, Hang ; Huang, Hongwei
Author_Institution :
Eng. Coll., Air Force Eng. Univ., Xi´´an, China
Volume :
6
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
Because the traditional evaluation of the Automatic Test System (ATS) just considered the fuzzification of the evaluation index, and ignored the randomicity and indetermination of the index, so a new method based on neural net and cloud model is proposed to solve the problem. An ameliorated neural net algorithm is used to get the weight of the index. Cloud model is used to express the quantificational data with qualitative index, and the fuzzification, randomicity and indetermination of the index are considered in the model. The experiment results show that it´s feasible and effective in the comprehensive evaluation of ATS.
Keywords :
automatic testing; fuzzy set theory; neural nets; random number generation; random processes; ameliorated neural net algorithm; automatic test system; cloud model; fuzzification; fuzzy comprehensive evaluation; indetermination; qualitative index; quantificational data; randomicity; Job shop scheduling; Processor scheduling; Cloud model; comprehensive evaluation; fuzzification and randomicity; indetermination; neural net;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5620572
Filename :
5620572
Link To Document :
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