摘要
本文详细阐述了采用BP神经网络和模糊神经网络进行城市需水预测的方法,并将这两种方法和灰色预测模型应用到石河子市需水预测的实证研究中。通过对这三种方法进行比较研究,发现在相关因素数据比较齐全时,两种神经网络的模拟结果精度较高,模糊神经网络方法的模拟精度最高。
Two forecasting methods of the urban water demand are presented which are back propagation network and fuzzy neural network , and the two methods and gray model method are used to estimate the water demand of Shihezi. The result of this case study shows that the method using the fuzzy neural network to forecasting urban water demand is better than gray model method when the historical data are sufficiant, and fuzzy neural network is the best one.
出处
《石河子大学学报（自然科学版）》
CAS
2006年第1期22-25,共4页
Journal of Shihezi University(Natural Science)
基金
国家"十五"科技攻关项目(2002BA901A37)资助
