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Assessment of input variables determination on the SVM model performance using PCA, Gamma test, and forward selection techniques for monthly stream flow prediction
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Retraction notice to “Results uncertainty of solid waste generation forecasting by hybrid of wavelet transform-ANFIS and wavelet transform-neural network”
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inferred← citeshttps://doi.org/10.1007/s12205-019-0804-9openalex-snapshot
Prediction of Ground Water Table Using NF-GMDH Based Evolutionary Algorithms
inferred← citeshttps://doi.org/10.1007/s12205-019-1327-0openalex-snapshot
Prediction of Scour Depth below River Pipeline using Support Vector Machine
inferred← citeshttps://doi.org/10.1007/s12517-014-1363-5openalex-snapshot
Determining the effective parameters and their optimal combination in rill erosion modeling
inferred← citeshttps://doi.org/10.1007/s12517-016-2601-9openalex-snapshot
Evaluating the support vector machine for suspended sediment load forecasting based on gamma test
inferred← citeshttps://doi.org/10.1007/s12517-016-2750-xopenalex-snapshot
Multi-time-scale analysis of hydrological drought forecasting using support vector regression (SVR) and artificial neural networks (ANN)
inferred← citeshttps://doi.org/10.1007/s12517-017-2990-4openalex-snapshot
Evaluation of dynamic regression and artificial neural networks models for real-time hydrological drought forecasting
inferred← citeshttps://doi.org/10.1007/s12517-020-05437-0openalex-snapshot
New input selection procedure for machine learning methods in estimating daily global solar radiation
inferred← citeshttps://doi.org/10.1007/s12665-011-1487-9openalex-snapshot
Active and online prediction of BOD5 in river systems using reduced-order support vector machine
inferred← citeshttps://doi.org/10.1007/s12665-016-5323-0openalex-snapshot
Flood hazard mapping in Jamaica using principal component analysis and logistic regression
inferred← citeshttps://doi.org/10.1007/s12665-017-6938-5openalex-snapshot
Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters
inferred← citeshttps://doi.org/10.1007/s12665-019-8474-yopenalex-snapshot
Evaluation of data-driven models (SVR and ANN) for groundwater-level prediction in confined and unconfined systems
inferred← citeshttps://doi.org/10.1007/s12665-019-8755-5openalex-snapshot
Spatiotemporal precipitation modeling by artificial intelligence-based ensemble approach
inferred← citeshttps://doi.org/10.1007/s12665-021-09625-3openalex-snapshot
Artificial intelligence for suspended sediment load prediction: a review
inferred← citeshttps://doi.org/10.1007/s12665-023-11222-5openalex-snapshot
Enhanced variational mode decomposition with deep learning SVM kernels for river streamflow forecasting
inferred← citeshttps://doi.org/10.1007/s12665-025-12173-9openalex-snapshot
Analysis and prediction of groundwater quality using machine learning algorithm for irrigation purposes
inferred← citeshttps://doi.org/10.1007/s13157-021-01499-2openalex-snapshot
Development of a Novel Fuzzy Logic-Based Wetland Health Assessment Approach for the Management of Freshwater Wetland Ecosystems
inferred← citeshttps://doi.org/10.1007/s13201-022-01593-8openalex-snapshot
Review on generating optimal operation for dam and reservoir water system: simulation models and optimization algorithms
inferred← citeshttps://doi.org/10.1007/s13201-023-02005-1openalex-snapshot
Multi-ahead electrical conductivity forecasting of surface water based on machine learning algorithms
inferred← citeshttps://doi.org/10.1007/s13201-024-02154-xopenalex-snapshot
Enhancing spatial streamflow prediction through machine learning algorithms and advanced strategies
inferred← citeshttps://doi.org/10.1007/s13762-018-2049-4openalex-snapshot
Prediction of water quality parameters using evolutionary computing-based formulations
inferred← citeshttps://doi.org/10.1007/s13762-019-02485-2openalex-snapshot
A novel algorithm for feature selection based on geographic distance metric: a case study of streamflow forecasting of Austria’s water resources
inferred← citeshttps://doi.org/10.1007/s13762-024-05725-2openalex-snapshot
Artificial intelligence integration in conventional wastewater treatment techniques: techno-economic evaluation, recent progress and its future direction
inferred← citeshttps://doi.org/10.1007/s40899-021-00506-yopenalex-snapshot
Application of optimized Support Vector Machine in monthly streamflow forecasting: using Autocorrelation Function for input variables estimation
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Assessment of machine learning models for short-term streamflow estimation: the case of Dez River in Iran
inferred← citeshttps://doi.org/10.1007/s40996-024-01685-2openalex-snapshot
Uncertainty Assessment of Ensemble Base Machine Learning Modeling for Multi-step Ahead Forecasting of Dam Reservoir Inflows
inferred← citeshttps://doi.org/10.1007/s41062-023-01195-6openalex-snapshot
Prediction of water quality parameters using support vector regression
inferred← citeshttps://doi.org/10.1007/s41742-025-00814-7openalex-snapshot
Improved Prediction of Groundwater Quality Index by Hybrid Machine Learning Models in a Coastal Region: A Case Study From Southern Turkey
inferred← citeshttps://doi.org/10.1007/s41748-024-00518-6openalex-snapshot
Advancing Deltaic Aquifer Vulnerability Mapping to Seawater Intrusion and Human Impacts in Eastern Nile Delta: Insights from Machine Learning and Hydrochemical Perspective
inferred← citeshttps://doi.org/10.1007/s42452-024-05994-zopenalex-snapshot
Evaluation of the support vector regression (SVR) and the random forest (RF) models accuracy for streamflow prediction under a data-scarce basin in Morocco
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Rainfall to runoff: a comprehensive review of AI and traditional models for inflow forecasting in semi-arid basin
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Concepts, procedures, and applications of artificial neural network models in streamflow forecasting
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Hybrid artificial intelligence models for predicting daily runoff
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Support vector regression model optimized with GWO versus GA algorithms: Estimating daily pan-evaporation
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Support vector machines in water quality management
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A workflow to address pitfalls and challenges in applying machine learning models to hydrology
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Prediction of discharge coefficient of triangular labyrinth weirs using Adaptive Neuro Fuzzy Inference System
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A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting
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Reliable prediction of carbon monoxide using developed support vector machine
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The use of soft computing to classification of some weeds based on video processing
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Hybrid SVM-CIPSO methods for optimal operation of reservoir considering unknown future condition
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Identifying pollution sources and predicting urban air quality using ensemble learning methods
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A novel cepstral-based technique for automatic cognitive load estimation
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Reflectance spectroscopy for assessing heavy metal pollution indices in mangrove sediments using XGBoost method and physicochemical properties
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Artificial intelligence based modeling for predicting the disinfection by-products in water
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Predicting aquatic toxicities of chemical pesticides in multiple test species using nonlinear QSTR modeling approaches
inferred← citeshttps://doi.org/10.1016/j.compag.2017.04.005openalex-snapshot
Daily suspended sediment concentration simulation using hydrological data of Pranhita River Basin, India
inferred← citeshttps://doi.org/10.1016/j.compag.2017.11.008openalex-snapshot
Monthly pan-evaporation estimation in Indian central Himalayas using different heuristic approaches and climate based models
inferred← citeshttps://doi.org/10.1016/j.compag.2018.04.019openalex-snapshot
Spatial and multi-depth temporal soil temperature assessment by assimilating satellite imagery, artificial intelligence and regression based models in arid area
inferred← citeshttps://doi.org/10.1016/j.compag.2018.05.017openalex-snapshot
Optimizing prediction of human assessments of dairy odors using input variable selection
inferred← citeshttps://doi.org/10.1016/j.conbuildmat.2022.126678openalex-snapshot
The prediction of durability to freeze–thaw of limestone aggregates using machine-learning techniques
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Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches
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Optimized SVR model for predicting dissolved oxygen levels using wavelet denoising and variable reduction: Taking the Minjiang River estuary as an example
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Solar radiation estimation in different climates with meteorological variables using Bayesian model averaging and new soft computing models
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Groundwater level forecasting in a data-scarce region through remote sensing data downscaling, hydrological modeling, and machine learning: A case study from Morocco
inferred← citeshttps://doi.org/10.1016/j.ejrh.2026.103662openalex-snapshot
Multi-factor impacts identification and runoff forecasting based on ensemble model: A case study of the source region of Yellow River
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.106780openalex-snapshot
Prediction of total dissolved solids, based on optimization of new hybrid SVM models
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Explore the relationship between fish community and environmental factors by machine learning techniques
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Improved PMI-based input variable selection approach for artificial neural network and other data driven environmental and water resource models
inferred← citeshttps://doi.org/10.1016/j.envsoft.2023.105854openalex-snapshot
FlowDyn: A daily streamflow prediction pipeline for dynamical deep neural network applications
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A post-processing machine learning framework for bias-correcting National Water Model outputs by accounting for dominant streamflow drivers
inferred← citeshttps://doi.org/10.1016/j.eswa.2014.02.047openalex-snapshot
Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS
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Rapid detection of Chinese-specific peony seed oil by using confocal Raman spectroscopy and chemometrics
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Groundwater level simulation and forecasting using interior search algorithm-least square support vector regression (ISA-LSSVR)
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Investigating the artificial intelligence methods for determining performance of the NZVI permeable reactive barriers
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Machine learning-enhanced GALDIT modeling for the Nile Delta aquifer vulnerability assessment in the Mediterranean region
inferred← citeshttps://doi.org/10.1016/j.ijsrc.2017.09.005openalex-snapshot
Predicting characteristics of dune bedforms using PSO-LSSVM
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Geochemical controls of groundwaters upwelling in saline environments: Case study the discharge playa of Sidi El Hani (Sahel, Tunisia)
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Quantification of sand fraction from seismic attributes using Neuro-Fuzzy approach
inferred← citeshttps://doi.org/10.1016/j.jbiomech.2013.07.036openalex-snapshot
Prediction of ground reaction forces during gait based on kinematics and a neural network model
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Exploring the application of soft computing techniques for spatial evaluation of groundwater quality variables
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Artificial intelligence based ensemble modeling of wastewater treatment plant using jittered data
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Using a deep convolutional network to predict the longitudinal dispersion coefficient
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Longitudinal dispersion coefficient modeling in natural streams via newly proposed explainable ensemble learning (ExEL) framework
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Physically interpretable machine learning algorithm on multidimensional non-linear fields
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A two-stage support-vector-regression optimization model for municipal solid waste management – A case study of Beijing, China
inferred← citeshttps://doi.org/10.1016/j.jenvman.2014.12.014openalex-snapshot
Modeling water quality in an urban river using hydrological factors – Data driven approaches
inferred← citeshttps://doi.org/10.1016/j.jenvman.2023.117739openalex-snapshot
Meta-analysis of engineered nanoparticles dynamic aggregation in freshwater-like systems using machine learning techniques
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Daily suspended sediment load prediction using artificial neural networks and support vector machines
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2013.04.052openalex-snapshot
A reduced-order adaptive neuro-fuzzy inference system model as a software sensor for rapid estimation of five-day biochemical oxygen demand
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2013.07.008openalex-snapshot
Regional estimation of groundwater arsenic concentrations through systematical dynamic-neural modeling
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2014.01.004openalex-snapshot
Evaluating influences of seasonal variations and anthropogenic activities on alluvial groundwater hydrochemistry using ensemble learning approaches
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Real-time multi-step-ahead water level forecasting by recurrent neural networks for urban flood control
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Modeling soil water content in extreme arid area using an adaptive neuro-fuzzy inference system
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2015.08.022openalex-snapshot
Data-driven input variable selection for rainfall–runoff modeling using binary-coded particle swarm optimization and Extreme Learning Machines
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Artificial intelligence based models for stream-flow forecasting: 2000–2015
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A wavelet–linear genetic programming model for sodium (Na+) concentration forecasting in rivers
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2016.05.052openalex-snapshot
Soil moisture deficit estimation using satellite multi-angle brightness temperature
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2016.07.045openalex-snapshot
An information theoretic approach to select alternate subsets of predictors for data-driven hydrological models
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2016.12.024openalex-snapshot
Choice of rainfall inputs for event-based rainfall-runoff modeling in a catchment with multiple rainfall stations using data-driven techniques
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2017.01.018openalex-snapshot
Physical and numerical modeling of performance of detention dams
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An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction
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Novel forecasting models for immediate-short-term to long-term influent flow prediction by combining ANFIS and grey wolf optimization
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Hybrid forecasting model for non-stationary daily runoff series: A case study in the Han River Basin, China
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Modelling of soil permeability using different data driven algorithms based on physical properties of soil
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Comparison of eight filter-based feature selection methods for monthly streamflow forecasting – Three case studies on CAMELS data sets
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Intelligent identification of effective reservoirs based on the random forest classification model
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Bayesian Network based modeling of regional rainfall from multiple local meteorological drivers
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Examination and comparison of binary metaheuristic wrapper-based input variable selection for local and global climate information-driven one-step monthly streamflow forecasting
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2021.126196openalex-snapshot
Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2021.126242openalex-snapshot
An emergency multi-objective compromise framework for reservoir operation under suddenly injected pollution
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2021.126370openalex-snapshot
Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models
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Combining two-stage decomposition based machine learning methods for annual runoff forecasting
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Evaluating the impact of improved filter-wrapper input variable selection on long-term runoff forecasting using local and global climate information
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Uncertainty assessment of optically active and inactive water quality parameters predictions using satellite data, deep and ensemble learnings
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Local scour around bridge abutments in vegetated beds under ice-covered flow conditions – An experimental study and mathematical assessment using machine learning methods
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A dynamic multi-objective inversion framework for seepage parameters based on monitoring data: case study of an earth-rockfill dam
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Mitigating environmental risks: Modeling the interaction of water quality parameters and land use cover
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Prognostication of waste water treatment plant performance using efficient soft computing models: An environmental evaluation
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Data pre-post processing methods in AI-based modeling of seepage through earthen dams
inferred← citeshttps://doi.org/10.1016/j.molliq.2015.06.001openalex-snapshot
Predicting acetyl cholinesterase enzyme inhibition potential of ionic liquids using machine learning approaches: An aid to green chemicals designing
inferred← citeshttps://doi.org/10.1016/j.polar.2022.100839openalex-snapshot
PCA-based SVM classification for simulated ice floes in front of sluice gates
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The potential of new ensemble machine learning models for effluent quality parameters prediction and related uncertainty
inferred← citeshttps://doi.org/10.1016/j.rineng.2025.105646openalex-snapshot
Prediction and analysis of punching shear capacity in steel fiber reinforced concrete slab using machine learning
inferred← citeshttps://doi.org/10.1016/j.rineng.2025.106345openalex-snapshot
Advancing Sub-Seasonal to Seasonal Streamflow Forecasting in Canada: A Review of Conventional and Emerging Approaches for Operational Applications
inferred← citeshttps://doi.org/10.1016/j.rineng.2026.111474openalex-snapshot
Concrete cracking risk analysis of a dam based on KABWO-SVM response surface and structural reliability method
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Evaluation of machine learning, information theory and multi-criteria decision analysis methods for flood susceptibility mapping under varying spatial scale of analyses
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Oversampling-based prediction of environmental complaints related to construction projects with imbalanced empirical-data learning
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Assessment of arsenic concentration in stream water using neuro fuzzy networks with factor analysis
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2016.03.219openalex-snapshot
Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques
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Design and implementation of a hybrid model based on two-layer decomposition method coupled with extreme learning machines to support real-time environmental monitoring of water quality parameters
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2019.133591openalex-snapshot
Simulating heavy metal concentrations in an aquatic environment using artificial intelligence models and physicochemical indexes
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