| 基于灰色RBF组合模型的城市用水量预测 |
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| 作者姓名： | 龙文 徐松金 |
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| 作者单位： | 1. 贵州财经学院贵州省经济系统仿真重点实验室,贵州贵阳,550004
2. 铜仁学院数学与计算机科学系,贵州铜仁,554300 |
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| 基金项目： | 国家自然科学基金资助项目 |
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| 摘 要： | 为解决城市用水量预测中单一方法预测精度不高的问题，建立了灰色径向基（RBF）神经网络组合模型。对比实验结果表明，灰色GM（1，1）模型、RBF神经网络模型和灰色RBF神经网络组合模型的平均相对误差分别为2．1222％，1．2562％和0．6821％。与灰色GM（1，1）模型和RBF神经网络相比，灰色RBF神经网络组合模型充分发挥了灰色系统的贫乏数据建模和RBF神经网络的高度非线性映射能力的双重优势，具有较高的预测精度，更适合用于城市用水量预测。
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| 关 键 词： | 灰色预测 RBF神经网络 组合模型 用水量预测 |
Prediction of urban water consumption based on grey-RBF combination model |
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| Authors: | Long Wen Xu Songjin |
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| Affiliation: | Long Wen1,Xu Songjin2 (1.Guizhou Key Laboratory of Economics System Simulation,College of Finance and Economics of Guizhou,Guiyang 550004,China,2.Department of Mathematics and Computer Science,Tongren Institute,Tongren 554300,China) |
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| Abstract: | In order to overcome the low forecasting precision by a single method,a new combination model based on grey-RBF neural network was developed for forecasting of urban water consumption.The result of comparison tests showed that the average relative errors of grey GM(1,1) model,RBF neural network model and grey-RBF neural network combination model were 2.122%,1.256% and 0.682% respectively.Compared with grey GM(1,1) model and RBF neural network model,the grey-RBF combination model could bring into full play t... |
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| Keywords: | grey prediction RBF neural network combination model prediction of water consumption |
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