长距离输水系统的神经网络模型研究

Study on Artificial Neural Network Models of Long-distance Water Supply System

常规特征线算法在仿真模拟长距离有压输水系统流量调节过渡过程时,存在计算时间较长等不足,故无法很好地满足实时控制和优化调度的需要.本文利用人工神经网络(ANN)所具有的高度非线性全局作用、良好的自适应性及联想记忆功能等优点,将人工神经网络引入到过渡过程的分析中,建立合适的神经网络模型,并通过该模型得出一系列计算成果.该成果与传统算法所得的结果相比较表明,人工神经网络在过渡流的分析中是可行的,并具有明显的优势.

In order to overcome the deficiency of general algorithm in simulating the transition process of unsteady pressure flow in a long:distance water supply system, the authors developed a model by applying the Artificial Neural Network (ANN) method. The ANN method was of global non:linearity function, self:adaptation and memorization. This ANN model was adopted to analyze the unsteady flow in a long:distance water supply system. Compared with the conventional method, the computational result showed that the ANN method was feasible and well applicable to the transition process of pressure flows.