Comparison of Groundwater Level Models Based on Artificial Neural Networks and ANFIS

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2015
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Abstract
Water table forecasting plays an important role in the management of groundwater resources in agricultural regions where there are drainage systems in river valleys. The results presented in this paper pertain to an area along the left bank of the Danube River, in the Province of Vojvodina, which is the northern part of Serbia. Two soft computing techniques were used in this research: an adaptive neurofuzzy inference system (ANFIS) and an artificial neural network (ANN) model for one-month water table forecasts at several wells located at different distances from the river. The results suggest that both these techniques represent useful tools for modeling hydrological processes in agriculture, with similar computing and memory capabilities, such that they constitute an exceptionally good numerical framework for generating high-quality models.
Reference Key
djurovic2015comparisonthe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Djurovic, Nevenka;Domazet, Milka;Stricevic, Ruzica;Pocuca, Vesna;Spalevic, Velibor;Pivic, Radmila;Gregoric, Enika;Domazet, Uros;
Journal the scientific world journal
Year 2015
DOI
DOI not found
URL
http://dx.doi.org/10.1155/2015/742138
Keywords
Medicine Technology Science geology

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