A Hybrid Neural Networks-Coevolution Genetic Algorithm for Multi Variables Robust Design Problem in Quality Engineering
Publish Year: 1388
نوع سند: مقاله ژورنالی
زبان: English
View: 109
This Paper With 18 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
این Paper در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JITM-1-1_008
تاریخ نمایه سازی: 26 بهمن 1400
Abstract:
In this study, a hybrid algorithm is presented to tackle multi-variables robust design problem. The proposed algorithm comprises neural networks (NNs) and co-evolution genetic algorithm (CGA) in which neural networks are as a function approximation tool used to estimate a map between process variables. Furthermore, in order to make a robust optimization of response variables, co-evolution algorithm is applied to solve constructed model of process. Results of CGA are compared with genetic algorithm (GA). This algorithm is tested in a case study of open-end spinning process.
Keywords:
Co evolution Genetic Algorithm , Genetic algorithm , neural networks , Quality Engineering , Robust optimization