Modelling discharge-sediment relationship using neural networks with artificial bee colony algorithm

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@Article{Kisi201294,
  author =       "Ozgur Kisi and Coskun Ozkan and Bahriye Akay",
  title =        "Modelling discharge-sediment relationship using neural
                 networks with artificial bee colony algorithm",
  journal =      "Journal of Hydrology",
  volume =       "428-429",
  pages =        "94--103",
  year =         "2012",
  ISSN =         "0022-1694",
  DOI =          "doi:10.1016/j.jhydrol.2012.01.026",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0022169412000698",
  keywords =     "genetic algorithms, genetic programming, Suspended
                 sediment, Modelling, Neural networks, Artificial bee
                 colony algorithm",
  abstract =     "Estimation of suspended sediment concentration carried
                 by a river is very important for many water resources
                 projects. The accuracy of artificial neural networks
                 (ANN) with artificial bee colony (ABC) algorithm is
                 investigated in this paper for modelling
                 discharge-suspended sediment relationship. The ANN-ABC
                 was compared with those of the neural differential
                 evolution, adaptive neuro-fuzzy, neural networks and
                 rating curve models. The daily stream flow and
                 suspended sediment concentration data from two
                 stations, Rio Valenciano Station and Quebrada Blanca
                 Station, were used as case studies. For evaluating the
                 ability of the models, mean square error and
                 determination coefficient criteria were used.
                 Comparison results showed that the ANN-ABC was able to
                 produce better results than the neural differential
                 evolution, neuro-fuzzy, neural networks and rating
                 curve models. The logarithm transformed data were also
                 used as input to the proposed ANN-ABC models. It was
                 found that the logarithm transform significantly
                 increased accuracy of the models in suspended sediment
                 estimation.",
}

Genetic Programming entries for Ozgur Kisi Coskun Ozkan Bahriye Akay

Citations