摘要
神经网络模型是一种非常有效的数据处理工具,但是存在结构确定困难的缺点.针对神经网络算法的这种缺点,提出了变结构神经网络模型.此模型增加了神经网络隐节点的决策变量,并对此决策变量进行松弛.在采用BP梯度算法确定神经网络结构的同时,确定网络参数.由于电缆的状态监测是时序数据,将此模型应用于电缆的状态监测过程中,能体现出较好的适应性.
Neural network model is an effective data processing method, but it has a shortcoming of difficult structure confirmation. This paper aims at this primary disadvantage of the neural network calculation, giving a variable structure neural network model, which model increases decisionmaking variable in allusion to the hidden nodes of neutral network, fixing network parameter while using BP gradient algorithm to fix the structure of neural network by means of slacking this decisionmaking variable. In applying this model to cable state detection which is time series data, in processing continuous changing data, this model has good adaptability.
出处
《上海电力学院学报》
CAS
2008年第1期57-60,64,共5页
Journal of Shanghai University of Electric Power
基金
上海市科学技术委员会西部项目资助计划
关键词
神经网络
BP算法
状态监测
neural network
BP calculation
state detection