Corrosion rate prediction model of grounding grid based on support vector machine optimized by artificial bee colony algorithm

被引:0
作者
Liu Y. [1 ]
Chen C. [1 ]
机构
[1] State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing
来源
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2019年 / 39卷 / 05期
关键词
Artificial bee colony algorithm; Corrosion rate; Grounding grid; Prediction model; Support vector machines;
D O I
10.16081/j.issn.1006-6047.2019.05.027
中图分类号
学科分类号
摘要
In order to improve the accuracy of corrosion rate prediction for grounding grid, firstly the corrosion diagnosis of grounding grid based on the theory of electric network is carried out, and the position of corrosion branches after diagnosis are taken as sampling points. Considering the limitation of reflecting the corrosion rate prediction of grounding grid only by soil physical and chemical properties, and based on the result of corrosion diagnosis, the ave-rage growth rate of resistance in grounding grid is proposed as one of the input characteristics of the prediction mo-del. Then the corrosion rate prediction model of grounding grid based on the support vector machine optimized by artificial bee colony algorithm is proposed. The test results show that compared with the BP neural network model and generalized regression neural network model, the proposed model has higher prediction precision and stability, and good applicability to solve the problem of corrosion rate prediction for grounding grid. © 2019, Electric Power Automation Equipment Press. All right reserved.
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页码:182 / 186and200
相关论文
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