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Evaluation Method of Multiobjective Functions’ Combination and Its Application in Hydrological Model Evaluation
المؤلفون المشاركون
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-23، 23ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-03-10
دولة النشر
مصر
عدد الصفحات
23
التخصصات الرئيسية
الملخص EN
Parameter optimization of a hydrological model is intrinsically a high dimensional, nonlinear, multivariable, combinatorial optimization problem which involves a set of different objectives.
Currently, the assessment of optimization results for the hydrological model is usually made through calculations and comparisons of objective function values of simulated and observed variables.
Thus, the proper selection of objective functions’ combination for model parameter optimization has an important impact on the hydrological forecasting.
There exist various objective functions, and how to analyze and evaluate the objective function combinations for selecting the optimal parameters has not been studied in depth.
Therefore, to select the proper objective function combination which can balance the trade-off among various design objectives and achieve the overall best benefit, a simple and convenient framework for the comparison of the influence of different objective function combinations on the optimization results is urgently needed.
In this paper, various objective functions related to parameters optimization of hydrological models were collected from the literature and constructed to nine combinations.
Then, a selection and evaluation framework of objective functions is proposed for hydrological model parameter optimization, in which a multiobjective artificial bee colony algorithm named RMOABC is employed to optimize the hydrological model and obtain the Pareto optimal solutions.
The parameter optimization problem of the Xinanjiang hydrological model was taken as the application case for long-term runoff prediction in the Heihe River basin.
Finally, the technique for order preference by similarity to ideal solution (TOPSIS) based on the entropy theory is adapted to sort the Pareto optimal solutions to compare these combinations of objective functions and obtain the comprehensive optimal objective functions’ combination.
The experiments results demonstrate that the combination 2 of objective functions can provide more comprehensive and reliable dominant options (i.e., parameter sets) for practical hydrological forecasting in the study area.
The entropy-based method has been proved that it is effective to analyze and evaluate the performance of different combinations of objective functions and can provide more comprehensive and impersonal decision support for hydrological forecasting.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Huo, Jiuyuan& Liu, Liqun. 2020. Evaluation Method of Multiobjective Functions’ Combination and Its Application in Hydrological Model Evaluation. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-23.
https://search.emarefa.net/detail/BIM-1138840
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Huo, Jiuyuan& Liu, Liqun. Evaluation Method of Multiobjective Functions’ Combination and Its Application in Hydrological Model Evaluation. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-23.
https://search.emarefa.net/detail/BIM-1138840
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Huo, Jiuyuan& Liu, Liqun. Evaluation Method of Multiobjective Functions’ Combination and Its Application in Hydrological Model Evaluation. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-23.
https://search.emarefa.net/detail/BIM-1138840
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1138840
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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