基于模糊神经网络的城市供水系统负荷预测

Loading Forecasting of Urban Water Supply based on Fuzzy Neuro Network

针对城市供水系统的复杂性、非线性、时变化性与多因素影响的特点，引入了模糊逻辑系统（ＦＬＳ）和人工神经网络（ＡＮＮ），将一种改进的最近邻聚类算法，用于城市水负荷预测，对短期、中长期水负荷的预测实验表明，该方法结构简单，精度高。

Abstract Aiming at the multi factor Influences on urban water supply system such as the complexity, non linearity, time variation etc an improved nearest neighbor calculation which the fuzzy logic system (FLS) and artificial neuro network (ANN) are conducted in has been adopted to estimate the loading of urban water supply The estimation experiments on short time and medium long term hydrography show that this method is simple to use with high accuracy