An Intelligent Optimizing Approach for Spinning Process Based on Immune Neural Network Expert System

摘要：

This paper presents an immune optimization method based neural network expert system for spinning production. A radial basis function neural network (RBFNN) is applied to build the double-RBFNN model and the immune operators are then introduced to enhance the adaptability and learning ability of the neural network model. The immune optimized neural network model is embedded in the expert system to adjust and deploy the main factors affecting the spinning performance, such as optimizing the spinning crafts. It is also used to predict the performance of the spinning process and help to obtain good predictions, compared with the actual value. Simulation results demonstrates that it can get the desired results for the process optimization. The method proposes a new idea in connection with the differential fiber spinning crafts optimization.

关键词： immune neural network expert system differentiation spinning production

作者: Bao-Qing Li Yong-Sheng Ding Xiao Liang Kuang-Rong Hao Hua-Ping Wang

作者单位: College of Information Sciences and Technology Engineering Research Center of Digitized Textile & Fa College of Material Science and Technology Donghua University Shanghai, Shanghai 201620, China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Automation Engineering(ICCAE 2011)(2011年第三届IEEE计算机与自动化工程国际会议)

会议地点: 重庆

会议语种:英文

页码: 23-27

在线出版日期: 2011-01-21（万方平台首次上网日期，不代表论文的发表时间）