城市需水量预测的混沌神经网络模型  

Prediction Model of Urban Water Con-sumption Based on Chaos Neural Network

作　　者：刘勇健[1] 沈军[1] 

机构地区：[1]广东工业大学建设学院,广东广州510643

出　　处：《水电能源科学》2005年第1期15-17,27,共4页Water Resources and Power

基　　金：广东省自然科学基金资金项目 ( 0 4 0 0 94 77) ;广东省重点学科基金资助项目 ( 2 0 2 16 )

摘　　要：将人工神经网络原理引入城市需水量预测中 ,针对 BP网络收敛速度慢、易陷入局部极小的缺陷 ,提出了基于混沌神经网络的城市需水量预测模型 ,该模型简便易行 ,收敛速度快、预测精度高 ,具有良好的应用前景。Theory of artificial neural network is introduced into prediction of urban water consumption in this paper. Since BP neural networks owns disadvantage of slow convergence and local minimization, the proposed prediction model of urban water consumption is based on chaos optimal method and BP algorithm. Typical examples prove that the model is a very effective and accurate water consumption forecast model and easy to handle with. This method is expected to be widely used in practice.

关 键 词：城市需水量 神经网络 混沌优化 时间序列 预测 

分 类 号：TV123.4[水利工程—水文学及水资源]