Regionalization by fuzzy expert system based approach optimized by genetic algorithm.

In recent years soft computing methods are being increasingly used to model complex hydrologic processes. These methods can simulate the real life processes without prior knowledge of the exact relationship between their components. The principal aim of this paper is perform hydrological regionaliza...

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Main Authors: Chavoshi, Sattar, Sulaiman, Wan Nor Azmin, Saghafian, Bahram, Sulaiman, Md. Nasir, Abd Manaf, Latifah
Format: Article
Language:English
Published: Elsevier 2013
Online Access:http://psasir.upm.edu.my/id/eprint/30640/1/Regionalization%20by%20fuzzy%20expert%20system%20based%20approach%20optimized%20by%20genetic%20algorithm.pdf
http://psasir.upm.edu.my/id/eprint/30640/
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spelling my.upm.eprints.306402015-09-08T09:14:15Z http://psasir.upm.edu.my/id/eprint/30640/ Regionalization by fuzzy expert system based approach optimized by genetic algorithm. Chavoshi, Sattar Sulaiman, Wan Nor Azmin Saghafian, Bahram Sulaiman, Md. Nasir Abd Manaf, Latifah In recent years soft computing methods are being increasingly used to model complex hydrologic processes. These methods can simulate the real life processes without prior knowledge of the exact relationship between their components. The principal aim of this paper is perform hydrological regionalization based on soft computing concepts in the southern strip of the Caspian Sea basin, north of Iran. The basin with an area of 42,400 sq. km has been affected by severe floods in recent years that caused damages to human life and properties. Although some 61 hydrometric stations and 31 weather stations with 44 years of observed data (1961–2005) are operated in the study area, previous flood studies in this region have been hampered by insufficient and/or reliable observed rainfall-runoff records. In order to investigate the homogeneity (h) of catchments and overcome incompatibility that may occur on boundaries of cluster groups, a fuzzy expert system (FES) approach is used which incorporates physical and climatic characteristics, as well as flood seasonality and geographic location. Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. In order to achieve the objective, a MATLAB programming code was developed which considers the heterogeneity criteria of less than 1 (H < 1) as the satisfying criteria. The adopted approach was found superior to the conventional hydrologic regionalization methods in the region because it employs greater number of homogeneity parameters and produces lower values of heterogeneity criteria. Elsevier 2013-04-12 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30640/1/Regionalization%20by%20fuzzy%20expert%20system%20based%20approach%20optimized%20by%20genetic%20algorithm.pdf Chavoshi, Sattar and Sulaiman, Wan Nor Azmin and Saghafian, Bahram and Sulaiman, Md. Nasir and Abd Manaf, Latifah (2013) Regionalization by fuzzy expert system based approach optimized by genetic algorithm. Journal of Hydrology, 486. pp. 271-280. ISSN 0022-1694; ESSN: 1879-2707 10.1016/j.jhydrol.2013.01.033
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description In recent years soft computing methods are being increasingly used to model complex hydrologic processes. These methods can simulate the real life processes without prior knowledge of the exact relationship between their components. The principal aim of this paper is perform hydrological regionalization based on soft computing concepts in the southern strip of the Caspian Sea basin, north of Iran. The basin with an area of 42,400 sq. km has been affected by severe floods in recent years that caused damages to human life and properties. Although some 61 hydrometric stations and 31 weather stations with 44 years of observed data (1961–2005) are operated in the study area, previous flood studies in this region have been hampered by insufficient and/or reliable observed rainfall-runoff records. In order to investigate the homogeneity (h) of catchments and overcome incompatibility that may occur on boundaries of cluster groups, a fuzzy expert system (FES) approach is used which incorporates physical and climatic characteristics, as well as flood seasonality and geographic location. Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. In order to achieve the objective, a MATLAB programming code was developed which considers the heterogeneity criteria of less than 1 (H < 1) as the satisfying criteria. The adopted approach was found superior to the conventional hydrologic regionalization methods in the region because it employs greater number of homogeneity parameters and produces lower values of heterogeneity criteria.
format Article
author Chavoshi, Sattar
Sulaiman, Wan Nor Azmin
Saghafian, Bahram
Sulaiman, Md. Nasir
Abd Manaf, Latifah
spellingShingle Chavoshi, Sattar
Sulaiman, Wan Nor Azmin
Saghafian, Bahram
Sulaiman, Md. Nasir
Abd Manaf, Latifah
Regionalization by fuzzy expert system based approach optimized by genetic algorithm.
author_facet Chavoshi, Sattar
Sulaiman, Wan Nor Azmin
Saghafian, Bahram
Sulaiman, Md. Nasir
Abd Manaf, Latifah
author_sort Chavoshi, Sattar
title Regionalization by fuzzy expert system based approach optimized by genetic algorithm.
title_short Regionalization by fuzzy expert system based approach optimized by genetic algorithm.
title_full Regionalization by fuzzy expert system based approach optimized by genetic algorithm.
title_fullStr Regionalization by fuzzy expert system based approach optimized by genetic algorithm.
title_full_unstemmed Regionalization by fuzzy expert system based approach optimized by genetic algorithm.
title_sort regionalization by fuzzy expert system based approach optimized by genetic algorithm.
publisher Elsevier
publishDate 2013
url http://psasir.upm.edu.my/id/eprint/30640/1/Regionalization%20by%20fuzzy%20expert%20system%20based%20approach%20optimized%20by%20genetic%20algorithm.pdf
http://psasir.upm.edu.my/id/eprint/30640/
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score 13.18916