The Gradual Optimization of Grounding Grip Corrosion Rate Forecasting Model

摘要：

　　A forecasting model of the gradual optimization algorithm is established to predict substation grounding grip corrosion rate.In this model,according to the Over Fittingphenomenon in the neural network limited soil corrosion sample data are randomly combined and the training stops when the training error and validation error are equal.The model of smaller errors will be chosen as the optimal model.As shown in the simulation,the general performance and fitting accuracy from the forecasting model meet requirements.

关键词： gradual optimization forecasting model training error validation error grounding grip corrosion rate

作者: Yan Aijun Du Jingyi Liu Rui Li Na Tang Xiaohua Liu Lei Li Zhizhong

作者单位: The Ground Engineering Laboratory, State Grid Company, Shaanxi Power Academyof Sciences, Xran 71005, College of Electrical and Control Engineering, Xran University of Science and Technology, Xian 7100 The Key Laboratory of Corrosion and Protection, Materials Science and Engineering College,Xian Univ

会议类型: 国际会议

会议名称: 2nd International Conference on Materials Engineering and Automatic Control (第二届材料工程与自动化控制国际会议)(ICMEAC2013)

会议地点: 济南

会议语种:英文

页码: 1075-1079

在线出版日期: 2013-05-18（万方平台首次上网日期，不代表论文的发表时间）