Developing an intelligent expert system for streamflow prediction, integrated in a dynamic decision support system for managing multiple reservoirs: A case study

作者：

Highlights：

• Extracting and using of time-dependent indices improved prediction accuracy.

• Pre-processing of data improved prediction accuracy.

• Intelligent selection of predictors via sensitivity analysis and data mining.

• Successful integration of a novel forecast expert system in an operation system.

摘要

•Extracting and using of time-dependent indices improved prediction accuracy.•Pre-processing of data improved prediction accuracy.•Intelligent selection of predictors via sensitivity analysis and data mining.•Successful integration of a novel forecast expert system in an operation system.

论文关键词：ANFIS,ARIMA,ANN,Hybrid model of ANN-ARIMA,Data mining,Streamflow prediction

论文评审过程：Received 23 June 2016, Revised 18 April 2017, Accepted 18 April 2017, Available online 19 April 2017, Version of Record 28 April 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.04.039