A machine code-based genetic programming for suspended sediment concentration estimation
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{Kisi2010939,
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author = "Ozgur Kisi and Aytac Guven",
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title = "A machine code-based genetic programming for suspended
sediment concentration estimation",
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journal = "Advances in Engineering Software",
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volume = "41",
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number = "7-8",
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pages = "939--945",
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year = "2010",
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note = "Advances in Structural Optimization",
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ISSN = "0965-9978",
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DOI = "doi:10.1016/j.advengsoft.2010.06.001",
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URL = "http://www.sciencedirect.com/science/article/B6V1P-50G0DYF-1/2/c917b48e2cfced4167ad3ab9ee02e797",
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keywords = "genetic algorithms, genetic programming, Suspended
sediment concentration, Modelling, Neuro-fuzzy, Neural
networks, Rating curve",
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abstract = "Correct estimation of suspended sediment concentration
carried by a river is very important for many water
resources projects. The application of linear genetic
programming (LGP), which is an extension to genetic
programming (GP) technique, for suspended sediment
concentration estimation is proposed in this paper. The
LGP is compared with those of the adaptive neuro-fuzzy,
neural networks and rating curve models. The daily
streamflow and suspended sediment concentration data
from two stations, Rio Valenciano Station and Quebrada
Blanca Station, operated by the US Geological Survey
(USGS) are used as case studies. The root mean square
errors (RMSE) and determination coefficient (R2)
statistics are used for evaluating the accuracy of the
models. Comparison of the results indicated that the
LGP performs better than the neuro-fuzzy, neural
networks and rating curve models. For the Rio
Valenciano and Quebrada Blanca Stations, it is found
that the LGP models with RMSE = 44.4 mg/l, R2 = 0.910
and RMSE = 13.9 mg/l, R2 = 0.952 in test period is
superior in estimating daily suspended sediment
concentrations than the best accurate neuro-fuzzy model
with RMSE = 52.0 mg/l, R2 = 0.876 and RMSE = 17.9 mg/l,
R2 = 0.929, respectively.",
- }
Genetic Programming entries for
Ozgur Kisi
Aytac Guven
Citations