一种城市需水量预测的模糊认知图方法

摘要/Abstract

摘要： 系统运作的状态数据是复杂因素相互作用的产物,需水量的变化受到多种因素相互影响。传统的基于时间序列预测方法预测变量较单一,忽略了系统各因素的因果关系。因此,文中提出了一种新的预测方法—模糊认知图(FCM),其恰好拥有这种特性,它是一种带权重值的模糊反馈推理机制,量化表示概念间的因果关系,模拟整个系统运转。文中将模糊认知图和遗传算法相结合构建城市需水量模型,搜集整理了2001－2010年间的数据进行训练,最后采用2011－2015年间的数据来进行验证与测试。结果表明:在五年平均相对误差方面,非线性趋势模型为5.91%,BP神经网络为1.83%,提出的方法为1.34%,因此所提方法的预测精度较高、泛化性能良好。根据实验数据分析可得,未来济南市对于水资源进行管理时,要在合理把控万元国内生产总值用水量和万元工业增加值用水量的同时,加大城市工业用水重复率和居民生活用水回收率。该模型为城市需水量的预测和分析提供了一种更有效的方法。

关键词: 城市需水量预测, 模糊认知图, 遗传算法

Abstract: The state data of system operation is the product of the interaction of complex factors,and the change of water demand is affected by many factors.The traditional time series prediction method has a single predictor variable,ignoring the causal relationship of various factors of the system.Therefore,this paper proposed a new prediction method,namely Fuzzy Cognitive Map (FCM),which exactly has this kind of feature.It is a fuzzy feedback reasoning mechanism with weight value,which quantifies the causal relationship between concepts and simulates the entire system is running.This paper combined the fuzzy cognitive map and the genetic algorithm to construct the urban water demand model,collected and organized the data at 2001~2010,and finally used the data at 2011~2015 for verification and test.The results show that in terms of the five-year average relative error,the nonlinear trend model is 5.91%,the BP neural network is 1.83%,and the method of this paper is 1.34%.Therefore,the prediction accuracy of this method is higher and the generalization performance is good.According to the analysis of experimental data,in the future,the management of water resources in Jinan City should properly control the water consumption of GDP and the water consumption of industrial added value,and increase the urban industrial water reuse rate and the domestic water recovery rate.This model provides a more efficient method for urban water demand forecasting and analysis.

Key words: Fuzzy cognitive map, Genetic algorithm, Urban water demand forecast

中图分类号:

TP3-05

韩慧健, 宋馨芳, 张慧. 一种城市需水量预测的模糊认知图方法[J]. 计算机科学, 2019, 46(11A): 47-51. https://doi.org/

HAN Hui-jian, SONG Xin-fang, ZHANG Hui. Fuzzy Cognitive Map Method for Forecasting Urban Water Demand[J]. Computer Science, 2019, 46(11A): 47-51. https://doi.org/

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