水资源保护2012，Vol.28Issue(2)：8-11,16,5.DOI:10.3969/j.issn.1004-6933.2012.02.002
等维新息径向基神经网络模型在需水预测中的应用
Application of equi-dimensional information renewal radial basis function neural network model to urban water demand forecast
摘要
Abstract
To solve the problems of errors increasing with the extension of the forecast cycle and inadequate protection against random factor interference when using the existing models for multi-cycle urban water demand forecast, an equi-dimensional information renewal radial basis function neural network model was proposed, and the clustering approach was used for system learning. This model was applied to the annual water demand forecast in Dongguan City. The results show that the model has higher forecast accuracy than the fundamental radial basis function neural network model, and its forecast errors do not increase with the extension of the forecast cycle.关键词
城市需水量/预测/动态等维新息径向基/神经网络模型Key words
urban water demand/ forecast/ dynamic equi-dimensional information renewal radial basis/ neural network model分类
建筑与水利引用本文复制引用
许银山,吕孙云,梅亚东,熊莹..等维新息径向基神经网络模型在需水预测中的应用[J].水资源保护,2012,28(2):8-11,16,5.基金项目
国家自然科学基金(50839005) （50839005）
