To improve the accuracy of runoff forecasting,an uncertain multiple linear regression(UMLR) model is presented in this study. The proposed model avoids the transfer of random error generated in the independent variabl...To improve the accuracy of runoff forecasting,an uncertain multiple linear regression(UMLR) model is presented in this study. The proposed model avoids the transfer of random error generated in the independent variable to the dependent variable, as this affects prediction accuracy. On this basis, an inexact two-stage stochastic programming(ITSP) model is used for crop planting structure optimization(CPSO) with the inputs that are interval flow values under different probabilities obtained from the UMLR model. The developed system, in which the UMLR model for runoff forecasting and the ITSP model for crop planting structure optimization are integrated, is applied to a real case study. The aim of the developed system is to optimize crops planting area with limited available water resources base on the downstream runoff forecasting in order to obtain the maximum system benefit in the future. The solution obtained can demonstrate the feasibility and suitability of the developed system, and help decision makers to identify reasonable crop planting structure under multiple uncertainties.展开更多
基金supported by the National Key Research and Development Plan of China (2016YFC0400207)the National Natural Science Foundation of China (51439006)the National High Technology Research and Development Program of China (2013AA102904)
文摘To improve the accuracy of runoff forecasting,an uncertain multiple linear regression(UMLR) model is presented in this study. The proposed model avoids the transfer of random error generated in the independent variable to the dependent variable, as this affects prediction accuracy. On this basis, an inexact two-stage stochastic programming(ITSP) model is used for crop planting structure optimization(CPSO) with the inputs that are interval flow values under different probabilities obtained from the UMLR model. The developed system, in which the UMLR model for runoff forecasting and the ITSP model for crop planting structure optimization are integrated, is applied to a real case study. The aim of the developed system is to optimize crops planting area with limited available water resources base on the downstream runoff forecasting in order to obtain the maximum system benefit in the future. The solution obtained can demonstrate the feasibility and suitability of the developed system, and help decision makers to identify reasonable crop planting structure under multiple uncertainties.
