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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Genetic Programming for Prediction of Water Flow and Transport of Solids in a Basin
verfasst von : Juan R. Rabuñal, Jerónimo Puertas, Daniel Rivero, Ignacio Fraga, Luis Cea, Marta Garrido
Erschienen in: New Challenges on Bioinspired Applications
Verlag: Springer Berlin Heidelberg
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One of the applications of Data Mining is the extraction of knowledge from time series [1][2]. The Evolutionary Computation (EC) and the Artificial Neural Networks (ANNs) have proved to be suitable in Data Mining for handling this type of series [3] [4]. This paper presents the use of Genetic Programming (GP) for the prediction of time series in the field of Civil Engineering where the predictive structure does not follow the classic paradigms. In this specific case, the GP technique is applied to two phenomenon that models the process where, for a specific area, the fallen rain concentrates and flows on the surface, and later from the water flows is predicted the solids transport. In this article it is shown the Genetic Programming technique use for the water flows and the solids transport prediction. It is achieved good results both in the water flow prediction as in the solids transport prediction.