相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Evaluating and predicting social behavior of arsenic affected communities: Towards developing arsenic resilient society
Sushant K. Singh et al.
EMERGING CONTAMINANTS (2022)
Living with arsenic in the environment: An examination of current awareness of farmers in the Bengal basin using hybrid feature selection and machine learning
Debasish Mishra et al.
ENVIRONMENT INTERNATIONAL (2021)
Integrated environmental modeling for efficient aquifer vulnerability assessment using machine learning
Won Seok Jang et al.
ENVIRONMENTAL MODELLING & SOFTWARE (2020)
Novel Hybrid Integration Approach of Bagging-Based Fisher's Linear Discriminant Function for Groundwater Potential Analysis
Wei Chen et al.
NATURAL RESOURCES RESEARCH (2019)
Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches
Binh Thai Pham et al.
CATENA (2019)
Large scale prediction of groundwater nitrate concentrations from spatial data using machine learning
Lukas Knoll et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2019)
Hybrid computational intelligence models for groundwater potential mapping
Binh Thai Pham et al.
CATENA (2019)
Assessing the role of risk perception in ensuring sustainable arsenic mitigation
Sushant K. Singh et al.
GROUNDWATER FOR SUSTAINABLE DEVELOPMENT (2019)
Applications of machine learning techniques to predict filariasis using socio-economic factors
Phani Krishna Kondeti et al.
EPIDEMIOLOGY AND INFECTION (2019)
Lead, cadmium and arsenic in human milk and their socio-demographic and lifestyle determinants in Lebanon
Maya Bassil et al.
CHEMOSPHERE (2018)
Developing robust arsenic awareness prediction models using machine learning algorithms
Sushant K. Singh et al.
JOURNAL OF ENVIRONMENTAL MANAGEMENT (2018)
Comparison and evaluation of landslide susceptibility maps obtained from weight of evidence, logistic regression, and artificial neural network models
Christos Polykretis et al.
NATURAL HAZARDS (2018)
Groundwater Arsenic Contamination in the Ganga River Basin: A Future Health Danger
Dipankar Chakraborti et al.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2018)
Assessment of groundwater nitrate contamination hazard in a semi-arid region by using integrated parametric IPNOA and data-driven logistic regression models
Hossein Mojaddadi Rizeei et al.
ENVIRONMENTAL MONITORING AND ASSESSMENT (2018)
A Comparison of Machine-Learning Methods to Select Socioeconomic Indicators in Cultural Landscapes
Ana D. Maldonado et al.
SUSTAINABILITY (2018)
A comparative study between popular statistical and machine learning methods for simulating volume of landslides
Ataollah Shirzadi et al.
CATENA (2017)
Developing sustainable models of arsenic-mitigation technologies in the Middle-Ganga Plain in India
Sushant K. Singh et al.
CURRENT SCIENCE (2017)
Development of enhanced groundwater arsenic prediction model using machine learning approaches in Southeast Asian countries
Yongeun Park et al.
DESALINATION AND WATER TREATMENT (2016)
Arsenic groundwater contamination and its health effects in Patna district (capital of Bihar) in the middle Ganga plain, India
Dipankar Chakraborti et al.
CHEMOSPHERE (2016)
Predicting Arsenic in Drinking Water Wells of the Central Valley, California
Joseph D. Ayotte et al.
ENVIRONMENTAL SCIENCE & TECHNOLOGY (2016)
Arsenic contamination of groundwater and its induced health effects in Shahpur block, Bhojpur district, Bihar state, India: risk evaluation
Dipankar Chakraborti et al.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2016)
Arsenic concentration in drinking water of Bihar: health issues and socio-economic problems
Barun Kumar Thakur et al.
JOURNAL OF WATER SANITATION AND HYGIENE FOR DEVELOPMENT (2016)
Arsenic in the human food chain, biotransformation and toxicology - Review focusing on seafood arsenic
Marianne Molin et al.
JOURNAL OF TRACE ELEMENTS IN MEDICINE AND BIOLOGY (2015)
Mapping composite vulnerability to groundwater arsenic contamination: an analytical framework and a case study in India
Sushant K. Singh et al.
NATURAL HAZARDS (2015)
Sustainability of arsenic mitigation interventions-an evaluation of different alternative safe drinking water options provided in Matlab, an arsenic hot spot in Bangladesh
Mohammed Hossain et al.
FRONTIERS IN ENVIRONMENTAL SCIENCE (2015)
Smoothness without Smoothing: Why Gaussian Naive Bayes Is Not Naive for Multi-Subject Searchlight Studies
Rajeev D. S. Raizada et al.
PLOS ONE (2013)
Health Risk Assessment Due to Groundwater Arsenic Contamination: Children Are at High Risk
Sushant Kumar Singh et al.
HUMAN AND ECOLOGICAL RISK ASSESSMENT (2012)
A GIS-based logistic regression model in rock-fall susceptibility mapping along a mountainous road: Salavat Abad case study, Kurdistan, Iran
Ataollah Shirzadi et al.
NATURAL HAZARDS (2012)
Multiple regression, ANN (RBF, MLP) and ANFIS models for prediction of swell potential of clayey soils
Isik Yilmaz et al.
EXPERT SYSTEMS WITH APPLICATIONS (2011)
Arsenic pollution of groundwater in Vietnam exacerbated by deep aquifer exploitation for more than a century
Lenny H. E. Winkel et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2011)
GIS-based spatial prediction of landslide susceptibility using logistic regression model
Seyedeh Zohreh Mousavi et al.
GEOMATICS NATURAL HAZARDS & RISK (2011)
Technical and Social Evaluation of Arsenic Mitigation in Rural Bangladesh
Md. Shafiquzzaman et al.
JOURNAL OF HEALTH POPULATION AND NUTRITION (2009)
Random forests and nearest shrunken centroids for the classification of sensor array data
Matteo Pardo et al.
SENSORS AND ACTUATORS B-CHEMICAL (2008)
Sustainability of arsenic mitigation in Bangladesh: Results of a functionality survey
Ahammadul Kabir et al.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH (2007)
A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas
D. P. Kanungo et al.
ENGINEERING GEOLOGY (2006)
Arsenic groundwater contamination in Middle Ganga Plain, Bihar, India: A future danger?
D Chakraborti et al.
ENVIRONMENTAL HEALTH PERSPECTIVES (2003)
Class prediction by nearest shrunken centroids, with applications to DNA microarrays
R Tibshirani et al.
STATISTICAL SCIENCE (2003)
Numerical methods in rock mechanics
L Jing et al.
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES (2002)