Conjunct application of machine learning and game theory in groundwater quality mapping

[1]  M. Abdo,et al.  Integrated machine learning–based model and WQI for groundwater quality assessment: ML, geospatial, and hydro-index approaches , 2023, Environmental Science and Pollution Research.

[2]  V. Gholami,et al.  Evaluation of machine learning algorithms for groundwater quality modeling , 2023, Environmental Science and Pollution Research.

[3]  S. Elsayed,et al.  Evaluation of Groundwater Quality for Irrigation in Deep Aquifers Using Multiple Graphical and Indexing Approaches Supported with Machine Learning Models and GIS Techniques, Souf Valley, Algeria , 2023, Water.

[4]  Duong Tran Anh,et al.  Possible Factors Driving Groundwater Quality and Its Vulnerability to Land Use, Floods, and Droughts Using Hydrochemical Analysis and GIS Approaches , 2022, Water.

[5]  Anees Ahmad,et al.  Potential health risk assessment, spatio-temporal hydrochemistry and groundwater quality of Yamuna river basin, Northern India. , 2022, Chemosphere.

[6]  S. Elsayed,et al.  Evaluation of groundwater quality for agricultural under different conditions using water quality indices, partial least squares regression models, and GIS approaches , 2022, Applied Water Science.

[7]  Saeid Janizadeh,et al.  Evaluating different machine learning algorithms for snow water equivalent prediction , 2022, Earth Science Informatics.

[8]  Juan Carlos Trabucco,et al.  Mapping of groundwater productivity potential with machine learning algorithms: A case study in the provincial capital of Baluchistan, Pakistan. , 2022, Chemosphere.

[9]  S. Sadeghi,et al.  Comparative prioritization of sub-watersheds based on Flood Generation potential using physical, hydrological and co-managerial approaches , 2022, Water Resources Management.

[10]  Jianhua Wu,et al.  Predictive modeling of groundwater nitrate pollution and evaluating its main impact factors using random forest. , 2021, Chemosphere.

[11]  Selçuk Demir,et al.  Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based on CPT data , 2022, Soil Dynamics and Earthquake Engineering.

[12]  N. Al‐Ansari,et al.  Groundwater level prediction using machine learning models: A comprehensive review , 2022, Neurocomputing.

[13]  R. Noori,et al.  An Efficient Data Driven-Based Model for Prediction of the Total Sediment Load in Rivers , 2022, Hydrology.

[14]  Z. Srdjevic,et al.  Water quality prediction based on Naïve Bayes algorithm. , 2022, Water science and technology : a journal of the International Association on Water Pollution Research.

[15]  R. P. Pant,et al.  Efficient water quality prediction models based on machine learning algorithms for Nainital Lake, Uttarakhand , 2022, Materials Today: Proceedings.

[16]  Subhan Danish,et al.  Assessment of Water Quality in Lake Qaroun Using Ground-Based Remote Sensing Data and Artificial Neural Networks , 2021, Water.

[17]  S. Bhawani,et al.  Various Natural and Anthropogenic Factors Responsible for Water Quality Degradation: A Review , 2021, Water.

[18]  Junxia Li,et al.  Prediction on the fluoride contamination in groundwater at the Datong Basin, Northern China: Comparison of random forest, logistic regression and artificial neural network , 2021 .

[19]  Qihao Weng,et al.  Spatial heterogeneity modeling of water quality based on random forest regression and model interpretation. , 2021, Environmental research.

[20]  Fatin I. Mahir,et al.  Surface and Ground Water Pollution: Causes and Effects of Urbanization and Industrialization in South Asia , 2021, Scientific Review.

[21]  M. Khazaei,et al.  Determination of flood probability and prioritization of sub-watersheds: A comparison of game theory to machine learning. , 2021, Journal of environmental management.

[22]  B. Pradhan,et al.  Machine learning algorithm for flash flood prediction mapping in Wadi El-Laqeita and surroundings, Central Eastern Desert, Egypt , 2021, Arabian Journal of Geosciences.

[23]  Mustakim,et al.  The Classification Status of River Water Quality in Riau Province Using Modified K-Nearest Neighbor Algorithm with STORET Modeling and Water Pollution Index , 2021 .

[24]  H. Qian,et al.  Groundwater quality assessment using a new integrated-weight water quality index (IWQI) and driver analysis in the Jiaokou Irrigation District, China. , 2021, Ecotoxicology and environmental safety.

[25]  P. Lochyński,et al.  Effects of drought on environmental health risk posed by groundwater contamination. , 2021, Chemosphere.

[26]  Y. P. Chua,et al.  Drinking Water Quality Mapping Using Water Quality Index and Geospatial Analysis in Primary Schools of Pakistan , 2020 .

[27]  M. Baghapour,et al.  Estimation of the groundwater quality index and investigation of the affecting factors their changes in Shiraz drinking groundwater, Iran , 2020 .

[28]  D. Adomako,et al.  Evolution of groundwater hydrogeochemistry and assessment of groundwater quality in the Anayari catchment , 2020 .

[29]  Z. Yaseen,et al.  Iran's Agriculture in the Anthropocene , 2020, Earth's Future.

[30]  A. A. Moghaddam,et al.  Groundwater quality assessment using random forest method based on groundwater quality indices (case study: Miandoab plain aquifer, NW of Iran) , 2020, Arabian Journal of Geosciences.

[31]  Il-Kyu Kim,et al.  Comparison of machine learning algorithms for Chl-a prediction in the middle of Nakdong River (focusing on water quality and quantity factors) , 2020 .

[32]  Gammoudi Safa,et al.  Assessment of urban groundwater vulnerability in arid areas: Case of Sidi Bouzid aquifer (central Tunisia) , 2020 .

[33]  Sk Ajim Ali,et al.  Analysing water-borne diseases susceptibility in Kolkata Municipal Corporation using WQI and GIS based Kriging interpolation , 2020, GeoJournal.

[34]  L. Luo,et al.  Evaluation of random forests for short-term daily streamflow forecasting in rainfall- and snowmelt-driven watersheds , 2020, Hydrology and Earth System Sciences.

[35]  K. Sarma,et al.  Qualitative assessment, geochemical characterization and corrosion-scaling potential of groundwater resources in Ghaziabad district of Uttar Pradesh, India , 2020 .

[36]  Alex B. McBratney,et al.  Game theory interpretation of digital soil mapping convolutional neural networks , 2020, SOIL.

[37]  S. Tweed,et al.  Degradation of groundwater quality in expanding cities in West Africa. A case study of the unregulated shallow aquifer in Cotonou , 2020 .

[38]  A. Embaby,et al.  Multi-criteria decision-making for the analysis of flash floods: A case study of Awlad Toq-Sherq, Southeast Sohag, Egypt , 2020 .

[39]  M. Kumar,et al.  Sulphate contamination in groundwater and its remediation: an overview , 2020, Environmental Monitoring and Assessment.

[40]  Z. O. Ojekunle,et al.  Assessment of physicochemical characteristics of groundwater within selected industrial areas in Ogun State, Nigeria , 2020 .

[41]  M. Vafakhah,et al.  Regional Analysis of Flow Duration Curves through Support Vector Regression , 2019, Water Resources Management.

[42]  V. Sunitha,et al.  Data on application of water quality index method for appraisal of water quality in around cement industrial corridor, Yerraguntla Mandal, Y.S.R District, A.P South India , 2019, Data in brief.

[43]  Xubo Gao,et al.  Geochemical modeling, source apportionment, health risk exposure and control of higher fluoride in groundwater of sub-district Dargai, Pakistan. , 2019, Chemosphere.

[44]  Evangelos Rozos,et al.  Machine Learning, Urban Water Resources Management and Operating Policy , 2019, Resources.

[45]  Lidia Morawska,et al.  New insights into the spatial distribution of particle number concentrations by applying non-parametric land use regression modelling. , 2019, The Science of the total environment.

[46]  Seyed Amir Naghibi,et al.  A Comparative Assessment of Random Forest and k-Nearest Neighbor Classifiers for Gully Erosion Susceptibility Mapping , 2019, Water.

[47]  M. Faouzi,et al.  Climate change projections in the Ghis-Nekkor region of Morocco and potential impact on groundwater recharge , 2019, Theoretical and Applied Climatology.

[48]  C. Moeck,et al.  A review of threats to groundwater quality in the anthropocene. , 2019, The Science of the total environment.

[49]  B. Saghafian,et al.  The Groundwater‒Energy‒Food Nexus in Iran’s Agricultural Sector: Implications for Water Security , 2019, Water.

[50]  Seyed Amir Naghibi,et al.  Water Resources Management Through Flood Spreading Project Suitability Mapping Using Frequency Ratio, k-nearest Neighbours, and Random Forest Algorithms , 2019, Natural Resources Research.

[51]  Bharti,et al.  An assessment of trace element contamination in groundwater aquifers of Saharanpur, Western Uttar Pradesh, India , 2019, Biocatalysis and Agricultural Biotechnology.

[52]  Alireza Bahadori,et al.  Prediction of water quality index (WQI) using support vector machine (SVM) and least square-support vector machine (LS-SVM) , 2019, International Journal of River Basin Management.

[53]  Nisar Muhammad,et al.  Hydrochemical properties of drinking water and their sources apportionment of pollution in Bajaur agency, Pakistan , 2019, Measurement.

[54]  Biswajeet Pradhan,et al.  A Novel Ensemble Artificial Intelligence Approach for Gully Erosion Mapping in a Semi-Arid Watershed (Iran) , 2019, Sensors.

[55]  Danial Jahed Armaghani,et al.  Random Forests and Cubist Algorithms for Predicting Shear Strengths of Rockfill Materials , 2019, Applied Sciences.

[56]  H. Khosravi,et al.  Assessing the ground water quality for pressurized irrigation systems in Kerman Province, Iran using GIS , 2019, Sustainable Water Resources Management.

[57]  Senén Barro,et al.  An extensive experimental survey of regression methods , 2019, Neural Networks.

[58]  M. Mesgari,et al.  Spatial variability analysis of precipitation and its concentration in Chaharmahal and Bakhtiari province, Iran , 2019, Theoretical and Applied Climatology.

[59]  R. Rooki,et al.  Evolving genetic programming and other AI-based models for estimating groundwater quality parameters of the Khezri plain, Eastern Iran , 2019, Environmental Earth Sciences.

[60]  R. A. Khan,et al.  Hydro-Geochemical Assessment of Groundwater Quality in Aseer Region, Saudi Arabia , 2018, Water.

[61]  Sudhir Kumar Singh,et al.  Assessment of groundwater quality for irrigation use: a peninsular case study , 2018, Applied Water Science.

[62]  Peiyue Li,et al.  Groundwater quality assessment for domestic and agricultural purposes in Yan’an City, northwest China: implications to sustainable groundwater quality management on the Loess Plateau , 2018, Environmental Earth Sciences.

[63]  Abdelkader Hamlat,et al.  Assessment of groundwater quality in a semiarid region of Northwestern Algeria using water quality index (WQI) , 2018, Applied Water Science.

[64]  S. Deswal,et al.  Groundwater quality in urban and rural areas of north-eastern Haryana (India): a review , 2018, ISH Journal of Hydraulic Engineering.

[65]  E. Omran,et al.  Evaluation of groundwater quality and its suitability for drinking and irrigation using GIS and geostatistics techniques in semiarid region of Neyshabur, Iran , 2018, Applied Water Science.

[66]  F. Howari,et al.  Hydrochemical processes determining the groundwater quality for irrigation use in an arid environment: The case of Liwa Aquifer, Abu Dhabi, United Arab Emirates , 2018, Groundwater for Sustainable Development.

[67]  H. Soleimani,et al.  Prediction of human exposure and health risk assessment to trihalomethanes in indoor swimming pools and risk reduction strategy , 2018, Human and Ecological Risk Assessment: An International Journal.

[68]  Peiyue Li,et al.  Hydrogeochemical Evaluation of Groundwater Quality for Drinking and Irrigation Purposes and Integrated Interpretation with Water Quality Index Studies , 2018, Environmental Processes.

[69]  A. Mohammadi,et al.  Data on assessment of groundwater quality with application of ArcGIS in Zanjan, Iran , 2018, Data in brief.

[70]  Mehdi Vafakhah,et al.  Regional flood frequency analysis using support vector regression in arid and semi-arid regions of Iran , 2018 .

[71]  Z. Jamshidzadeh,et al.  Groundwater quality assessment using the potability water quality index (PWQI): a case in the Kashan plain, Central Iran , 2018, Environmental Earth Sciences.

[72]  Matthew P. Miller,et al.  Predicting redox‐sensitive contaminant concentrations in groundwater using random forest classification , 2017 .

[73]  Osisanwo F.Y,et al.  Supervised Machine Learning Algorithms: Classification and Comparison , 2017 .

[74]  Martin Kappas,et al.  Comparison of Multiple Linear Regression, Cubist Regression, and Random Forest Algorithms to Estimate Daily Air Surface Temperature from Dynamic Combinations of MODIS LST Data , 2017, Remote. Sens..

[75]  Jianhua Wu,et al.  Lake water quality assessment: a case study of Shahu Lake in the semiarid loess area of northwest China , 2017, Environmental Earth Sciences.

[76]  S. Sadeghi,et al.  Sub-watershed prioritization based on sediment yield using game theory , 2016 .

[77]  Paraskevas Tsangaratos,et al.  Comparison of a logistic regression and Naïve Bayes classifier in landslide susceptibility assessments: The influence of models complexity and training dataset size , 2016 .

[78]  B. Parker,et al.  Geophysical and geochemical studies to delineate seawater intrusion in Bagoush area, northwestern coast, Egypt. , 2016 .

[79]  V. Wagh,et al.  Evaluating groundwater suitability for the domestic, irrigation, and industrial purposes in Nanded Tehsil, Maharashtra, India, using GIS and statistics , 2016, Arabian Journal of Geosciences.

[80]  Jan Adamowski,et al.  Intelligent Soft Computing Models in Water Demand Forecasting , 2016 .

[81]  N. Chandrasekar,et al.  Hydro-geochemistry and application of water quality index (WQI) for groundwater quality assessment, Anna Nagar, part of Chennai City, Tamil Nadu, India , 2015, Applied Water Science.

[82]  B. Pradhan,et al.  Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines , 2015 .

[83]  Yutaka Ichikawa,et al.  Farmers׳ perception of drought impacts, local adaptation and administrative mitigation measures in Maharashtra State, India , 2014 .

[84]  Mohamed Shehata Abd El Fatah,et al.  Applications of hydrogeochemical modeling to assessment geochemical evolution of the Quaternary aquifer system in Belbies area, East Nile Delta, Egypt , 2014 .

[85]  Abhay K. Singh,et al.  Hydrogeochemical investigation and groundwater quality assessment of Pratapgarh district, Uttar Pradesh , 2014, Journal of the Geological Society of India.

[86]  A. Davraz,et al.  Groundwater quality assessment and its suitability in Çeltikçi plain (Burdur/Turkey) , 2014, Environmental Earth Sciences.

[87]  Solomon Tesfamariam,et al.  Predicting copper concentrations in acid mine drainage: a comparative analysis of five machine learning techniques , 2013, Environmental Monitoring and Assessment.

[88]  Najmeh Mahjouri,et al.  Waste Load Allocation in Rivers using Fallback Bargaining , 2013, Water Resources Management.

[89]  M. Mahato,et al.  Evaluation of hydrogeochemical processes and groundwater quality in the Jhansi district of Bundelkhand region, India , 2013, Environmental Earth Sciences.

[90]  Wai Kin Ung,et al.  Freshwater Algal Bloom Prediction by Support Vector Machine in Macau Storage Reservoirs , 2012 .

[91]  C. Daughney,et al.  Groundwater age for identification of baseline groundwater quality and impacts of land-use intensification – The National Groundwater Monitoring Programme of New Zealand , 2012 .

[92]  M. Nagamani,et al.  Chemical characteristics of groundwater and assessment of groundwater quality in Varaha River Basin, Visakhapatnam District, Andhra Pradesh, India , 2012, Environmental Monitoring and Assessment.

[93]  Boris Schröder,et al.  How can statistical models help to determine driving factors of landslides , 2012 .

[94]  Bojan Srdjevic,et al.  Identifying the Criteria Set for Multicriteria Decision Making Based on SWOT/PESTLE Analysis: A Case Study of Reconstructing A Water Intake Structure , 2012, Water Resources Management.

[95]  K. V. Jitheshlal,et al.  Evaluation of groundwater quality and its suitability for drinking and agricultural use in the coastal stretch of Alappuzha District, Kerala, India , 2012, Applied Water Science.

[96]  D. Rahimi Potential ground water resources: (Case study: Shahrekord plain) , 2012 .

[97]  Edith Elkind,et al.  Choosing Collectively Optimal Sets of Alternatives Based on the Condorcet Criterion , 2011, IJCAI.

[98]  P. Döll,et al.  Groundwater use for irrigation - a global inventory , 2010 .

[99]  Kaveh Madani,et al.  Game theory and water resources , 2010 .

[100]  Reynold Cheng,et al.  Naive Bayes Classification of Uncertain Data , 2009, 2009 Ninth IEEE International Conference on Data Mining.

[101]  B. De Baets,et al.  Wetland vegetation distribution modelling for the identification of constraining environmental variables , 2008, Landscape Ecology.

[102]  Panayiotis E. Pintelas,et al.  Combining Bagging and Boosting , 2007 .

[103]  Rida Laraki,et al.  A theory of measuring, electing, and ranking , 2007, Proceedings of the National Academy of Sciences.

[104]  T. Subramani,et al.  Groundwater quality and its suitability for drinking and agricultural use in Chithar River Basin, Tamil Nadu, India , 2005 .

[105]  L. Breiman Random Forests , 2001, Encyclopedia of Machine Learning and Data Mining.

[106]  Leonard E. Trigg,et al.  Naive Bayes for regression , 1998 .

[107]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[108]  S. Karthikeyan,et al.  PHYSICOCHEMICAL ANALYSIS OF GROUNDWATER QUALITY OF VELLIANGADU AREA IN COIMBATORE DISTRICT, TAMILNADU, INDIA , 2019, Rasayan Journal of Chemistry.

[109]  Chen Lianjun Research on Snow Extracting Methods on the Basis of Random Forests Algorithm , 2016 .

[110]  F. Ramadan,et al.  Sedimentological and Hydrogeochemical Studies of the Quaternary Groundwater Aquifer in El Salhyia Area, Sharkia Governorate, Egypt , 2016 .

[111]  K. Diamantaras,et al.  RAINFALL–RUNOFF MODELING USING SUPPORT VECTOR REGRESSION AND ARTIFICIAL NEURAL NETWORKS , 2012 .

[112]  L. Pei-yue,et al.  Application of Set Pair Analysis Method Based on Entropy Weight in Groundwater Quality Assessment -A Case Study in Dongsheng City, Northwest China , 2011 .

[113]  Janusz A. Starzyk,et al.  Water resource planning and management using motivated machine learning , 2010 .