四川理工学院学报：自然科学版2012，Vol.25Issue(1)：63-66,4.
基于BP神经网络的输电线路覆冰增长模型研究
Study on Transmission Line Ice Accretion Mode Based on BP Neural Network
摘要
Abstract
After analyzing the deficiency of existing prediction accuracy of ice accretion on transmission lines and the superiority of neural network for nonlinear variable mapping, a new method based on BP neural network which taked the Levenberg-Marquardt learning algorithm was proposed. This new prediction model was practiced by the ice growth data of experiment. Using the convergent prediction model, a successful ice growth shows that there are 7 groups of prediction error less than lmm, whic The prediction simulation verified that this new prediction model is a in tbe prediction and prevention research prediction experiment was set up. The simulation result h is much better than the 3 groups of Makkonoe model effective model. This new model plays a significant role关键词
输电线路/覆冰增长/BP神经网络/Levenberg—Marquardt/预测Key words
transmission line/ice accretion/BP neural network/L-M algorithm/prediction分类
信息技术与安全科学引用本文复制引用
罗毅,姚毅,李莺,王锴,邱玲..基于BP神经网络的输电线路覆冰增长模型研究[J].四川理工学院学报：自然科学版,2012,25(1):63-66,4.基金项目
四川省电力公司资助项目 （）
人工智能实验室运行和开放式研究基金 （）
