Comprehensive evaluation of Automatic Test System based on neural net and cloud model
Huayong Xie, Mingqing Xiao, Hang Yu, Hongwei Huang · 2010
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.