Estimation of pan evaporation using soft computing tools
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Chaudhari:2012:IJHST,
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author = "Narhari Chaudhari and Shreenivas Londhe and
Kanchan Khare",
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title = "Estimation of pan evaporation using soft computing
tools",
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year = "2013",
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month = feb # "~28",
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volume = "2",
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journal = "International Journal of Hydrology Science and
Technology",
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issue = "4",
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pages = "373--390",
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keywords = "genetic algorithms, genetic programming, pan
evaporation, soft computing, artificial neural
networks, ANNs, penman's equation, water resources
management, water management, evaporation estimation.",
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ISSN = "2042-7816",
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publisher = "Inderscience Publishers",
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bibsource = "OAI-PMH server at www.inderscience.com",
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language = "eng",
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URL = "http://www.inderscience.com/link.php?id=52375",
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DOI = "DOI:10.1504/IJHST.2012.052375",
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abstract = "Estimation of evaporation plays a key role in managing
water resources projects. Traditionally, evaporation is
determined using theoretical and empirical techniques
as well as by pan observations. Practically, it is
difficult to install evaporation pans at every location
and empirical approach like Penman's equation is data
intensive. This necessitates the use of an alternative
approach, which can make use of readily available data
and estimate evaporation reasonably with limited data.
Major objective of the present study is to estimate
evaporation using the soft computing tools of
artificial neural networks (ANN) and genetic
programming (GP) making use of the measured climatic
parameters and to compare the results with traditional
empirical techniques. The results indicate that the
models developed using the soft computing tools of ANN
and GP worked reasonably well for estimation of
evaporation compared to empirical methods. GP works
slightly better for higher values of pan evaporation
compared to ANN.",
- }
Genetic Programming entries for
Narhari Chaudhari
S N Londhe
K C Khare
Citations