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吴 凡, 陈伏龙, 张志君, 龙爱华, 何新林.基于改进灰色模型的石河子市需水量预测水资源与水工程学报[J].,2020,31(3):76-82
基于改进灰色模型的石河子市需水量预测
Water demand prediction of Shihezi City based on improved grey model
  
DOI:10.11705/j.issn.1672-643X.2020.03.11
中文关键词:  灰色模型  需水量预测  变权弱化缓冲算子  指标分析法  石河子市
英文关键词:grey model  water demand prediction  variable weight weakening buffer operator  index analysis method  Shihezi City
基金项目:国家自然科学基金项目(51769029、51769030); 国家重点研发计划项目(2017YFC0404301); 石河子大学高层次人才科研启动资金项目(RCZK2018C23);自治区研究生科研创新项目(XJ2019G113)
作者单位
吴 凡1, 陈伏龙1, 张志君1, 龙爱华1,2, 何新林1 (1.石河子大学 水利建筑工程学院 新疆 石河子 832000 2.中国水利水电科学研究院流域水循环模拟与调控国家重点实验室 北京 100038) 
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中文摘要:
      针对城市需水预测原始序列波动性大、两阶段弱化缓冲算子的灰色模型对序列预处理强度难以把控的问题,在建模过程中引入变权弱化缓冲算子,通过研究人员的定性分析确定权重,实现对算子作用强度的控制,从而提高模型预测的精度。基于石河子市2011-2018年用水统计资料,分别建立了传统的灰色模型、二阶弱化缓冲算子的灰色模型、变权弱化缓冲算子的灰色模型,并结合指标分析法对城市需水量进行了预测。结果表明:改进后的模型较其他两种模型精度有所提高,并能在后续的预测中保持其稳定性和精度,与指标分析法预测结果差距小。石河子市需水量预测研究可为区域水资源规划与调度提供可靠的科学依据。
英文摘要:
      The original sequence of urban water demand prediction fluctuates greatly and it is difficult for the grey model with two-stage weakening buffer operator to control the intensity of sequence preprocessing. Therefore, the variable weight weakening buffer operator was introduced into the modelling process, in which the weight of the operator was determined by the qualitative analysis of the researchers, and the action intensity of the operator was hereby controlled, so is the accuracy of the model prediction. Based on the statistical data of water use in Shihezi City from 2011 to 2018, we established the conventional grey model, the grey model with second-order weakening buffer operator and the improved grey model with variable weight weakening buffer operator respectively. With the combination of index analysis method, the urban water demand of Shihezi City was predicted. The results show that the accuracy of the improved model is higher than that of the other two models, and the stability and accuracy of the improved model maintains the same level in the subsequent predictions. Furthermore, the difference of the prediction results between the improved model and the index analysis method is small. This study of water demand prediction can provide a reliable reference for the planning and dispatching of regional water resources in Shihezi City.
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