| 基于RBF神经网络的城市需水量预测研究 |
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| 引用本文： | 张俊艳,韩文秀.基于RBF神经网络的城市需水量预测研究[J].内蒙古农业大学学报(自然科学版),2006,27(2):90-93. |
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| 作者姓名： | 张俊艳 韩文秀 |
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| 作者单位： | 天津大学管理学院,天津,300072 |
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| 摘 要： | 鉴于RBF神经网络强大的非线性逼近能力及能够避免陷入局部最优的特点，建立了基于RBF神经网络的城市需水量预测模型，为提高神经网络的收敛速度及精度，利用退火遗传算法对网络进行了优化，并以天津市的城市需水量预测为例，进行了实例研究。
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| 关 键 词： | RBF神经网络 需水量 模拟退火 预测 |
| 文章编号： | 1009-3575(2006)02-0090-04 |
| 收稿时间： | 2006-03-13 |
| 修稿时间： | 2006年3月13日 |
STUDY ON THE WATER DEMAND FORECASTING OF URBAN BASED ON THE RBF NEURAL NETWORK |
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| ZHANG Jun-yan,HAN Wen-xiu.STUDY ON THE WATER DEMAND FORECASTING OF URBAN BASED ON THE RBF NEURAL NETWORK[J].Journal of Inner Mongolia Agricultural University(Natural Science Edition),2006,27(2):90-93. |
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| Authors: | ZHANG Jun-yan HAN Wen-xiu |
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| Institution: | School of Management, Tianjin University, Tianjin 300072,China |
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| Abstract: | Since the RBF Neural Networks has the property of nonlinear approximation and avoiding to fall in local optimum, water demand forecasting model for urban based on RBF Neural network was set up. And in order to improve the precision and converge speed of the network, the simulated annealing - genetic algorithm was applied to the optimization of the network. Finally, taking the water demand forecasting of Tianjin as the example the effectiveness of the method was tested. |
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| Keywords: | RBF neural network Water demand simulated - annealing - genetic algorithm forecasting |
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