Soft Computing tools in Rainfall-runoff Modeling
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- @Article{Jothiprakash:2009:ISHjhe,
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author = "V. Jothiprakash and R. Magar",
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title = "Soft Computing tools in Rainfall-runoff Modeling",
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journal = "ISH Journal of Hydraulic Engineering",
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year = "2009",
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volume = "15",
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number = "sup1",
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pages = "84--96",
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keywords = "genetic algorithms, genetic programming",
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publisher = "Taylor \& Francis",
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organisation = "Indian Society for Hydraulics",
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DOI = "doi:10.1080/09715010.2009.10514970",
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abstract = "The use of rainfall-runoff models in the decision
making process of water resources planning and
management has become increasingly indispensable.
Rainfall-runoff modeling in the broad sense started at
the end of 19th century and till today there are
various types of models based on their mechanism, input
data and other modeling requirements. These type of
models range from physical, conceptual, empirical
models and more sophisticated models like Artificial
Neural Network (ANN), Adaptive Neuro Fuzzy Inference
System (ANFIS), Genetic Programming (GP), Model Tree
(MT), Support Vector Machine (SVM) and recently Chaos
theory. The primary aim of this paper is to review the
recent works on Rainfall-Runoff modeling using soft
computing techniques.",
- }
Genetic Programming entries for
V Jothiprakash
Rajendra B Magar
Citations