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The Genetic Algorithm and Its Application to Calibrating Conceptual Rainfall‐Runoff Models
Author(s) -
Wang Q. J.
Publication year - 1991
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/91wr01305
Subject(s) - genetic algorithm , survival of the fittest , selection (genetic algorithm) , calibration , algorithm , surface runoff , computer science , meta optimization , conceptual model , mathematical optimization , data mining , mathematics , machine learning , statistics , ecology , biology , evolutionary biology , database
The genetic algorithm is a search procedure based on the mechanics of natural selection and natural genetics, which combines an artificial survival of the fittest with genetic operators abstracted from nature. In this paper, a genetic algorithm for function optimization is introduced and applied to calibration of a conceptual rainfall‐runoff model for data from a particular catchment. All seven parameters of the model are optimized. The results show that the genetic algorithm can be efficient and robust.