A systematic mapping of water quality prediction using computational intelligence techniques

  • Ivan Dario Lopez Universidad del Cauca
  • Apolinar Figueroa Universidad del cauca
  • Juan Carlos Corrales Universidad del Cauca
Keywords: water quality, computational intelligence, forecasting, complex adaptive systems


Due to the renewable nature of water, this resource has been treated and managed as if it were unlimited; however, increase the indiscriminate use has brought with it a rapid deterioration in quality; so as predicting water quality has a very important role for many socio-economic sectors that depend on the use of the precious liquid. In this study, a systematic literature mapping was performed about water quality prediction using computational intelligence techniques, including those used to calibrate predictive models in order to improve accuracy. Based on research questions formulated in the systematic mapping, a gap is identified oriented to creation of an adaptive mechanism for predicting water quality that can be applied in different water uses without raised the accuracy of the predictions is affected.

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  • Author Biographies

    Ivan Dario Lopez, Universidad del Cauca
    Grupo de Ingeniería Telemática - Universidad del Cauca, Cargo: Investigador
    Apolinar Figueroa, Universidad del cauca
    Universidad del Cauca, Profesor titular
    Juan Carlos Corrales, Universidad del Cauca
    Universidad del Cauca, Profesor titular
How to Cite
Lopez, I. D., Figueroa, A., & Corrales, J. C. (2016). A systematic mapping of water quality prediction using computational intelligence techniques. Revista Ingenierías Universidad De Medellín, 15(28), 35-51. https://doi.org/10.22395/rium.v15n28a2


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