2018
DOI: 10.1061/(asce)he.1943-5584.0001591
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Long-Term Groundwater-Level Forecasting in Shallow and Deep Wells Using Wavelet Neural Networks Trained by an Improved Harmony Search Algorithm

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Cited by 27 publications
(5 citation statements)
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References 69 publications
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“…The presence of the dominant autoregressive component creates the perfect condition for obtaining a very high forecast performance even with high LTs. A good modeling performance in deep and relatively isolated aquifers (with respect to shallow ones) was also found by Rakhshandehroo et al ().…”
Section: Resultssupporting
confidence: 68%
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“…The presence of the dominant autoregressive component creates the perfect condition for obtaining a very high forecast performance even with high LTs. A good modeling performance in deep and relatively isolated aquifers (with respect to shallow ones) was also found by Rakhshandehroo et al ().…”
Section: Resultssupporting
confidence: 68%
“…Both obtained encouraging results, indicating the suitability of NARX for predicting GW levels. Rakhshandehroo et al () used wavelet ANNs to predict the GW level in a shallow well in Florida and a deep well in Arkansas, concluding that noisy GW fluctuations in the shallow well caused higher error, which led to their obtaining the highest accuracy for the deep well.…”
Section: Introductionmentioning
confidence: 99%
“…A combined ANN with the wavelet transform technique (WANN) was relatively recently proposed to predict GWL where decomposed datasets with different resolutions for input are introduced (Khalil et al 2015; Nourani and Mousavi 2016; Rakhshandehroo et al 2018; Rajaee et al 2019). Hybrid approaches combining different models and techniques were also developed to further improve the prediction performance of GWL (Babovic et al 2001; Meshgi et al 2014; Nourani and Mousavi 2016; Wang et al 2017).…”
Section: Introductionmentioning
confidence: 99%
“…The fluctuation and the consequent prediction of the water table is one of the key problems of hydrological environment management [1]. Reliable prediction methods of the water table play significant roles in terms of groundwater planning and comprehensive management [2].…”
Section: Introductionmentioning
confidence: 99%
“…The Copula Function can be viewed as a multivariate probability distribution with uniform marginal in the interval [0,1]. In 2003, the first application of the Copula Function in the field of hydrology was undertaken [12].…”
Section: Introductionmentioning
confidence: 99%