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Water 2017, 9(7), 541; https://doi.org/10.3390/w9070541

A Hybrid Model for Forecasting Groundwater Levels Based on Fuzzy C-Mean Clustering and Singular Spectrum Analysis

1
University of Belgrade-Faculty of Mining and Geology, Đušina 7, 11000 Belgrade, Serbia
2
Čedomir Cvijović, Department of Geodesy, Belgrade University College of Applied Studies in Civil Engineering and Geodesy, Hajduk Stanka 2, 11000 Belgrade, Serbia
*
Author to whom correspondence should be addressed.
Received: 27 April 2017 / Revised: 11 July 2017 / Accepted: 15 July 2017 / Published: 19 July 2017
(This article belongs to the Special Issue Modeling of Water Systems)
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Abstract

Having the ability to forecast groundwater levels is very significant because of their vital role in basic functions related to efficiency and the sustainability of water supplies. The uncertainty which dominates our understanding of the functioning of water supply systems is of great significance and arises as a consequence of the time-unbalanced water consumption rate and the deterioration of the recharge conditions of captured aquifers. The aim of this paper is to present a hybrid model based on fuzzy C-mean clustering and singular spectrum analysis to forecast the weekly values of the groundwater level of a groundwater source. This hybrid model demonstrates how the fuzzy C-mean can be used to transform the sequence of the observed data into a sequence of fuzzy states, serving as a basis for the forecasting of future states by singular spectrum analysis. In this way, the forecasting efficiency is improved, because we predict the interval rather than the crisp value where the level will be. It gives much more flexibility to the engineers when managing and planning sustainable water supplies. A model is tested by using the observed weekly time series of the groundwater source, located near the town of Čačak in south-western Serbia. View Full-Text
Keywords: general drawdown; groundwater level; forecasting; fuzzy states; C-mean fuzzy clustering; singular spectrum analysis general drawdown; groundwater level; forecasting; fuzzy states; C-mean fuzzy clustering; singular spectrum analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Polomčić, D.; Gligorić, Z.; Bajić, D.; Cvijović, Č. A Hybrid Model for Forecasting Groundwater Levels Based on Fuzzy C-Mean Clustering and Singular Spectrum Analysis. Water 2017, 9, 541.

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