A Comparative Study of Groundwater Level Forecasting Using Data-Driven Models Based on Ensemble Empirical Mode Decomposition

A Comparative Study of Groundwater Level Forecasting Using Data-Driven Models Based on Ensemble Empirical Mode Decomposition

The reliable and accurate prediction of groundwater levels is important to improve water-use efficiency in the development and management of water resources. Three nonlinear time-series intelligence hybrid models were proposed to predict groundwater level fluctuations through a combination of ensemb...

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Bibliographic Details
Main Authors:	Yicheng Gong, Zhongjing Wang, Guoyin Xu, Zixiong Zhang
Format:	Article
Language:	English
Published:	MDPI AG 2018-06-01
Series:	Water
Subjects:	groundwater level ensemble empirical mode decomposition artificial neural network support vector machine adaptive neuro fuzzy inference system
Online Access:	http://www.mdpi.com/2073-4441/10/6/730

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