A survey of water level fluctuation predicting in Urmia Lake using support vector machine with firefly algorithm
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- @Article{Kisi:2015:AMC,
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author = "Ozgur Kisi and Jalal Shiri and Sepideh Karimi and
Shahaboddin Shamshirband and Shervin Motamedi and
Dalibor Petkovic and Roslan Hashim",
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title = "A survey of water level fluctuation predicting in
Urmia Lake using support vector machine with firefly
algorithm",
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journal = "Applied Mathematics and Computation",
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volume = "270",
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pages = "731--743",
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year = "2015",
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ISSN = "0096-3003",
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DOI = "doi:10.1016/j.amc.2015.08.085",
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URL = "http://www.sciencedirect.com/science/article/pii/S0096300315011418",
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abstract = "Forecasting lake level at various horizons is a
critical issue in navigation, water resource planning
and catchment management. In this article, multistep
ahead predictive models of predicting daily lake levels
for three prediction horizons were created. The models
were developed using a novel method based on support
vector machine (SVM) coupled with firefly algorithm
(FA). The FA was applied to estimate the optimal SVM
parameters. Daily water-level data from Urmia Lake in
north western Iran were used to train, test and
validate the used technique. The prediction results of
the SVM-FA models were compared to the genetic
programming (GP) and artificial neural networks (ANNs)
models. The experimental results showed that an
improvement in the predictive accuracy and capability
of generalization can be achieved by the SVM-FA
approach in comparison to the GP and ANN in 1 day ahead
lake level forecast. Moreover, the findings indicated
that the developed SVM-FA models can be used with
confidence for further work on formulating a novel
model of predictive strategy for lake level
prediction.",
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keywords = "genetic algorithms, genetic programming, Urmia Lake,
Time series, Prediction, Support vector machine,
Firefly algorithm",
- }
Genetic Programming entries for
Ozgur Kisi
Jalal Shiri
Sepideh Karimi
Shahaboddin Shamshirband
Shervin Motamedi
Dalibor Petkovic
Roslan Hashim
Citations