电子科技2025，Vol.38Issue(5)：8-14,30,8.DOI:10.16180/j.cnki.issn1007-7820.2025.05.002
基于改进鲸鱼算法优化的接地网腐蚀速率预测
Corrosion Rate Prediction of Grounding Grid Based on Improved Whale Algorithm Optimization
摘要
Abstract
In order to improve the accuracy of predicting the corrosion rate of substation grounding grids and solve the problems of traditional BP(Back Propagation)neural networks easily falling into local optima and traditional algorithms randomly initializing populations affecting prediction accuracy,this study proposes an improved whale opti-mization algorithm to optimize the BP neural network for predicting the corrosion rate of substation grounding grids.An improved whale optimization algorithm is developed using chaotic mapping to initialize whale population,impro-ving nonlinear factor to adjust adaptive weights,and enhancing search by Levay flight.Corrosion prediction model of grounding grid based on the improved whale optimization algorithm to optimize the BP neural network is established.The corrosion data of grounding network of 72 substations are simulated and analyzed.The results show that the aver-age relative error of the improved model is 1.84%,the global maximum relative error is 3.86%,and the root-mean-square error is 0.139 02,which is significantly lower than that of the traditional model,proving the feasibility of the proposed model.关键词
变电站/接地网/腐蚀速率/改进鲸鱼算法/BP神经网络/预测模型/混沌映射/非线性因子Key words
substation/grounding grid/corrosion rate/improved whale algorithm/BP neural network/prediction model/chaotic mapping/nonlinear factors分类
计算机与自动化引用本文复制引用
张海博,潘鹏程,郑峰..基于改进鲸鱼算法优化的接地网腐蚀速率预测[J].电子科技,2025,38(5):8-14,30,8.基金项目
国家水运安全工程技术研究中心开放基金(B2022002) （B2022002）
宜昌市自然科学基金(A22-3-008) Open Fund of the National Water Transport Safety Engineering Tech-nology Research Center(B2022002) （A22-3-008）
Natural Science Foundation of Yichang(A22-3-008) （A22-3-008）
