摘要
基于神经网络技术建立了浮运结构的重心知识库和稳性参数知识库 ,用于计算潮汐电站厂房浮运结构在浮运和沉放过程中的稳定性 .该知识库克服了公式计算的局限性 ,无需预知模型的形式 ,建模简单 ,易于程序化 .计算实例表明 。
This paper establishes the knowledge base of floating caisson stability based on neural net work to analyse the floating stability of the floating caisson of tidal power plants during floating and sinking. This knowledge base need not know the form of the model in advance and it overcomes the limitation of formulas. The establishing method is simple and easy for programming. The results show that the prediction of the floating stability is more accurate by the base based on the BP neural network.
关键词
浮运结构
知识库
浮运稳定性
神经网络
潮汐电站
floating caisson
knowledge base
floating stability
neural network
tidal power plant
