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基于PCCs-DEMATEL指标筛选的BP神经网络用水量预测

作  者：
崔惠敏;薛惠锋;王磊;赵臣啸
关键词：
BP神经网络;DEMATEL方法;皮尔逊相关系数;指数平滑法;用水量预测
摘  要：
以面向决策支持的用水量趋势预测为研究目标,采用从定性到定量的综合集成方法,将各指标变化率作为处理单元,运用PCCs-DEMATEL(皮尔逊相关系数-决策试验评估)方法对统计指标筛选,以BP神经网络构建预测模型,与赋权指数平滑法预测模型进行比较分析.模型在广州市的运用实例表明,基于PCCs-DEMATEL指标筛选的BP神经网络用水量预测模型可以更好地预测以年为单位的地区用水量,为水资源决策分析提供可靠的数据支撑.
作  者：
CUI Hui-min;XUE Hui-feng;WANG Lei;ZHAO Chen-xiao;Institute of Economics and Management,Xi'an University of Technology;China Academy of Aerospace System Science and Engineering;
单  位：
CUI Hui-min%XUE Hui-feng%WANG Lei%ZHAO Chen-xiao%Institute of Economics and Management,Xi'an University of Technology%China Academy of Aerospace System Science and Engineering
关键词：
BP neural network;;DEMATEL method;;Pearson correlation coefficient;;exponential smoothing method;;water consumption prediction
摘  要：
The research objective of this paper is forecasting the water consumption trend for decision support. The synthesis method from qualitative to quantitative is adopted. The change rate of each index is taken as the processing unit,and the statistical index is screened by PCCs-DEMATEL method. The BP neural network is used to construct annual water consumption prediction model,and compared with the weighted exponential smoothing method. The application of the model in Guangzhou shows that the BP neural network water consumption prediction model based on PCCs-DEMATEL index screening can better predict the regional annual water consumption,and provide reliable data supporting for water resources decision-making and analysis.

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