重庆大学学报2016，Vol.39Issue(6)：27-33,7.DOI:10.11835/j.issn.1000-582X.2016.06.004
神经网络自变量输入模式的视电阻率求解算法
Solution algorithm of apparent resistivity based on independent variable input mode of neural network
摘要
Abstract
According to the relationship between the response and the independent variables in transient electromagnetic field theory,a BP neural network with nonlinear equation model was proposed to solve the resistivity.By constructing a single-input-single-output network structure,a neural network with current normalized induced voltage at different time points as input and the apparent resistivity as the output was set up to simulate the secondary eddy current curve of the transient electromagnetic field.The accuracy of the trained network was verified by the data calculated by numerical computation,and the training accuracies and the convergence speeds of different algorithms were compared.The effectiveness of the proposed algorithm was verified by the experiments in an air-raid shelter in Chongqing University.The presented solution algorithm avoids calculation of complex electromagnetic field or numerical inverse problem,and realizes fast calculation of resistivity.关键词
瞬变电磁场/人工神经网络/反向传播/视电阻率/自变量输入Key words
transient electromagnetic field/artificial neural networks/backpropagation/apparent resistivity/independent variable input分类
信息技术与安全科学引用本文复制引用
曹敏,秦善强,胡绪权,付志红,王浩文..神经网络自变量输入模式的视电阻率求解算法[J].重庆大学学报,2016,39(6):27-33,7.基金项目
国家自然科学基金项目（51277189）；输配电装备及系统安全与新技术国家重点实验室自主研究重点项目（2007DA10512714103）。Supported by National Natural Science Foundation of China（51277189）and Key Independent Research Project of State Key Laboratory of Power Transmission Equipment ＆ System Security and New Tech-nology（2007DA10512714103）． （）
