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Correlation approach in predictor selection for groundwater level forecasting in areas threatened by water deficits
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Extreme gradient boosting (Xgboost) model to predict the groundwater levels in Selangor Malaysia
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The use of the Hellwig's method for feature selection in the detection of myeloma bone destruction based on radiographic images
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Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations
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Environmental health risk posed by contamination of the individual water wells
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Effects of drought on environmental health risk posed by groundwater contamination
inferredcites →https://doi.org/10.1016/j.ejrh.2015.07.007openalex-snapshot
Hydrological predictions for small ungauged watersheds in the Sudanian zone of the Volta basin in West Africa
inferredcites →https://doi.org/10.1016/j.geog.2016.07.005openalex-snapshot
Groundwater level prediction of landslide based on classification and regression tree
inferredcites →https://doi.org/10.1016/j.jhydrol.2011.06.013openalex-snapshot
A wavelet neural network conjunction model for groundwater level forecasting
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Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)
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A new artificial intelligence strategy for predicting the groundwater level over the Rafsanjan aquifer in Iran
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Studies regarding correct selection of statistical methods for the needs of increasing the efficiency of identification of land for consolidation—A case study in Poland
inferredcites →https://doi.org/10.1016/j.measurement.2020.108163openalex-snapshot
Relating groundwater levels with meteorological parameters using ANN technique
inferredcites →https://doi.org/10.1016/j.neucom.2014.05.026openalex-snapshot
An integrated wavelet-support vector machine for groundwater level prediction in Visakhapatnam, India
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Rainfall Prediction in Lahore City using Data Mining Techniques
inferredcites →https://doi.org/10.1515/jwld-2017-0012openalex-snapshot
Assessing the suitability of extreme learning machines (ELM) for groundwater level prediction
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Drought in Polish Forests in 2015
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The Reaction of Groundwater to Several Months’ Meteorological Drought in Poland
inferredcites →https://doi.org/10.2166/hydro.2008.006openalex-snapshot
Improving groundwater level forecasting with a feedforward neural network and linearly regressed projected precipitation
inferredcites →https://doi.org/10.2166/hydro.2010.034openalex-snapshot
Monthly groundwater level prediction using ANN and neuro-fuzzy models: a case study on Kerman plain, Iran
inferredcites →https://doi.org/10.2166/hydro.2017.102openalex-snapshot
Prediction of groundwater levels using evidence of chaos and support vector machine
inferredcites →https://doi.org/10.2166/hydro.2018.002openalex-snapshot
Semi-seasonal groundwater forecast using multiple data-driven models in an irrigated cropland
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GRNN Model for prediction of groundwater fluctuation in the state of Uttarakhand of India using GRACE data under limited bore well data
inferredcites →https://doi.org/10.2478/sggw-2018-0029openalex-snapshot
Analysis of the use of selected reservoirs in the Wielkopolska province
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Portable Analyzer for On-Site Determination of Dissolved Organic Carbon—Development and Field Testing
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Electropolishing of Stainless Steel in Laboratory and Industrial Scale
inferredcites →https://doi.org/10.3390/w13020139openalex-snapshot
Deterministic Analysis and Uncertainty Analysis of Ensemble Forecasting Model Based on Variational Mode Decomposition for Estimation of Monthly Groundwater Level
inferredcites →https://doi.org/10.3390/w13060778openalex-snapshot
Assessment of Hellwig Method for Predictors’ Selection in Groundwater Level Time Series Forecasting
inferredcites →https://doi.org/10.5194/hess-14-1931-2010openalex-snapshot
Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 1: Concepts and methodology
inferredcites →https://doi.org/10.7163/przg.2018.3.5openalex-snapshot
Zmienność czasowa i przestrzenna opadów atmosferycznych w Wielkopolsce w latach 1981–2014 = Temporal and spatial variability of atmospheric precipitation in Wielkopolska in the 1981–2014 period
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4791941openalex-extracted
Determining the Groundwater Level in Hilly and Plain Areas from Multi-Source Observation Data Combined with a Rf-Pso-Grnn Hybrid Approach
inferred← citeshttps://doi.org/10.2139/ssrn.4803508openalex-extracted
Groundwater Level Projection Under Climate Change Conditions Adopting a Hybrid Random Forest and Genetic Algorithm Model(Case Study: Silakhor Plain)
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Exploring the Twin Deficits Hypothesis Through Machine Learning: A New Approach to Economic Forecasting
inferred← citeshttps://doi.org/10.1007/s12665-025-12653-yopenalex-snapshot
Trends, challenges, and opportunities in groundwater level modeling with machine learning
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A systematic review of machine learning models for groundwater level prediction
inferred← citeshttps://doi.org/10.1016/j.envsoft.2024.106264openalex-snapshot
Variable sensitivity analysis in groundwater level projections under climate change adopting a hybrid machine learning algorithm
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Assessment of shallow groundwater aquifer in an arid environment, Western Saudi Arabia
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2023.168760openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.watres.2024.121249openalex-snapshot
Groundwater level forecasting with machine learning models: A review
inferred← citeshttps://doi.org/10.1109/wccest66994.2025.11389928openalex-snapshot
Transformative Insights into Groundwater Prediction in India
inferred← citeshttps://doi.org/10.1145/3607720.3607777openalex-snapshot
A review of Machine learning models and parameters for groundwater issues
inferred← citeshttps://doi.org/10.21203/rs.3.rs-8119285/v1openalex-snapshot
Denoising of Groundwater Level Data Using Wavelet Transform, SSA, and VMD: A Python-Based Approach
inferred← citeshttps://doi.org/10.31223/x5nt2bopenalex-snapshot
A Systematic Review of Machine Learning Algorithms in Groundwater Level Simulations and Forecasting
inferred← citeshttps://doi.org/10.3390/app16104583openalex-snapshot
Groundwater Level Prediction with Optimized Input Variable Combinations Using GS-LSTM and TOPSIS
inferred← citeshttps://doi.org/10.3390/su141811598openalex-snapshot
Daily Groundwater Level Prediction and Uncertainty Using LSTM Coupled with PMI and Bootstrap Incorporating Teleconnection Patterns Information
inferred← citeshttps://doi.org/10.3390/w18020139openalex-snapshot
Forecasting Groundwater Levels: A Comparison Between Support Vector Regression and Numerical Model
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