Genetic programming in water resources engineering: A state-of-the-art review
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{DANANDEHMEHR:2018:JH,
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author = "Ali {Danandeh Mehr} and Vahid Nourani and
Ercan Kahya and Bahrudin Hrnjica and Ahmed M. A. Sattar and
Zaher Mundher Yaseen",
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title = "Genetic programming in water resources engineering: A
state-of-the-art review",
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journal = "Journal of Hydrology",
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volume = "566",
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pages = "643--667",
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year = "2018",
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keywords = "genetic algorithms, genetic programming, Hydrology,
Hydraulics, Hydroclimatology, Water resources
engineering",
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ISSN = "0022-1694",
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DOI = "doi:10.1016/j.jhydrol.2018.09.043",
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URL = "http://www.sciencedirect.com/science/article/pii/S0022169418307376",
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abstract = "The state-of-the-art genetic programming (GP) method
is an evolutionary algorithm for automatic generation
of computer programs. In recent decades, GP has been
frequently applied on various kind of engineering
problems and undergone speedy advancements. A number of
studies have demonstrated the advantage of GP to solve
many practical problems associated with water resources
engineering (WRE). GP has a unique feature of
introducing explicit models for nonlinear processes in
the WRE, which can provide new insight into the
understanding of the process. Considering continuous
growth of GP and its importance to both water industry
and academia, this paper presents a comprehensive
review on the recent progress and applications of GP in
the WRE fields. Our review commences with brief
explanations on the fundamentals of classic GP and its
advanced variants (including multigene GP, linear GP,
gene expression programming, and grammar-based GP),
which have been proven to be useful and frequently used
in the WRE. The representative papers having wide range
of applications are clustered in three domains of
hydrological, hydraulic, and hydroclimatological
studies, and outlined or discussed at each domain.
Finally, this paper was concluded with discussions of
the optimum selection of GP parameters and likely
future research directions in the WRE are suggested",
- }
Genetic Programming entries for
Ali Danandeh Mehr
Vahid Nourani
Ercan Kahya
Bahrudin Hrnjica
Ahmed M Abdel Sattar
Zaher Mundher Yaseen
Citations