遗传算法在大坝安全监控神经网络预报模型建立中的应用

The application of genetic algorithm in establishment of neural network forecast model for dam safety monitoring

本文基于遗传算法思想 ,采用浮点数矩阵表示编码 ,在遗传算法的进化过程中加入一定的约束条件等方法 ,探讨了网络结构的设计和学习 .经实例分析 ,在用于建立大坝安全监控预报模型的前馈神经网络设计中 ,该方法在满足一定约束条件下 ,能同时有效地寻找合适的网络结构和相应的参数 (神经网络的权值和阈值 ) ,且在精度和速度上都有较大的提高 ,为实现实时在线分析评价大坝的安全性态提供了有力的技术支持 .

By using floating point matrix for coding and introducing some restriction conditions to the calculation process, a method for promoting the design and study capability of network structure is developed. The application shows that this method is effective for simultaneously determining the network structure and corresponding parameters during establishment of neural network forecast model, if specific restriction conditions can be satisfied. This method significantly promotes the speed and precision of the calculation and provides the real time on line assessment of dam safety with a useful technical support.