The Optimization of Plastic Injection Molding Process Based on Support Vector Machine and Genetic Algorithm

摘要：

The paper presents the radial basis kernel parameters of the Support vector machine (SVM) regression model employed to determine the complex and nonlinear relationships between the injection molding parameters and the defects of plastic injection molded parts, whereas genetic algorithm (GA) is applied to determine a set of optimal nuclear parameters for SVM. Then, an approximate analysis model is established, and it is proved effective by numerical examples of the plastic injection molded parts. All these explored an effective method of numerical simulation model for optimization of the plastic injection molding process.

作者: Yi mei Zhi shan

作者单位: College of Mechanical Engineering, Guizhou University, Guiyang 550003, China

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 1258-1261

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）