Multiobjective Optimal Algorithm for Automatic Calibration of Daily Streamflow Forecasting Model

Yi Liu, Jun Guo, Huaiwei Sun, Wei Zhang, Yueran Wang and Jianzhong Zhou

Mathematical Problems in Engineering, 2016, vol. 2016, 1-13

Abstract:

Single-objection function cannot describe the characteristics of the complicated hydrologic system. Consequently, it stands to reason that multiobjective functions are needed for calibration of hydrologic model. The multiobjective algorithms based on the theory of nondominate are employed to solve this multiobjective optimal problem. In this paper, a novel multiobjective optimization method based on differential evolution with adaptive Cauchy mutation and Chaos searching (MODE-CMCS) is proposed to optimize the daily streamflow forecasting model. Besides, to enhance the diversity performance of Pareto solutions, a more precise crowd distance assigner is presented in this paper. Furthermore, the traditional generalized spread metric (SP) is sensitive with the size of Pareto set. A novel diversity performance metric, which is independent of Pareto set size, is put forward in this research. The efficacy of the new algorithm MODE-CMCS is compared with the nondominated sorting genetic algorithm II (NSGA-II) on a daily streamflow forecasting model based on support vector machine (SVM). The results verify that the performance of MODE-CMCS is superior to the NSGA-II for automatic calibration of hydrologic model.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:8215308

DOI: 10.1155/2016/8215308

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