Ensemble Boosting and Bagging Based Machine Learning Models for Groundwater Potential Prediction

A Comparative Study between Frequency Ratio Model and Gradient Boosted Decision Trees with Greedy Dimensionality Reduction in Groundwater Potential Assessment

(2020) Shruti Sachdeva et al.   WATER RESOURCES MANAGEMENT

Application of rotation forest with decision trees as base classifier and a novel ensemble model in spatial modeling of groundwater potential

(2019) Seyed Amir Naghibi et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Inverse method using boosted regression tree and k-nearest neighbor to quantify effects of point and non-point source nitrate pollution in groundwater

(2019) Alireza Motevalli et al.   JOURNAL OF CLEANER PRODUCTION

GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models

(2018) Wei Chen et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Groundwater potential mapping using a novel data-mining ensemble model

(2018) Mojtaba Dolat Kordestani et al.   HYDROGEOLOGY JOURNAL

Mapping Groundwater Potential Using a Novel Hybrid Intelligence Approach

(2018) Shaghayegh Miraki et al.   WATER RESOURCES MANAGEMENT

Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes

(2018) Dennis H. Murphree et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Remote Sensing and GIS Based Groundwater Potential Zone Mapping in Ariyalur District, Tamil Nadu

(2018) G. Gnanachandrasamy et al.   JOURNAL OF THE GEOLOGICAL SOCIETY OF INDIA

Self-Learning Random Forests Model for Mapping Groundwater Yield in Data-Scarce Areas

(2018) Maher Ibrahim Sameen et al.   Natural Resources Research

Insights to fracture stimulation design in unconventional reservoirs based on machine learning modeling

(2018) Shuhua Wang et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

GIS-based groundwater potential mapping using artificial neural network and support vector machine models: the case of Boryeong city in Korea

(2017) Saro Lee et al.   Geocarto International

Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)

(2017) Bahareh Kalantar et al.   Geomatics Natural Hazards & Risk

gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework

(2016) Benjamin Hofner et al.   Journal of Statistical Software

Assessment of Groundwater Potential Based on Multicriteria Decision Making Model and Decision Tree Algorithms

(2016) Huajie Duan et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

A comparison between index of entropy and catastrophe theory methods for mapping groundwater potential in an arid region

(2015) Alaa M. Al-Abadi et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Remote Sensing and GIS Based Groundwater Potential & Recharge Zones Mapping Using Multi-Criteria Decision Making Technique

(2015) Rajat Agarwal et al.   WATER RESOURCES MANAGEMENT

Application of GIS based data driven evidential belief function model to predict groundwater potential zonation

(2014) Haleh Nampak et al.   JOURNAL OF HYDROLOGY

Generalized additive models for location, scale and shape for high dimensional data-a flexible approach based on boosting

(2012) Andreas Mayr et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS

A knowledge-driven GIS modeling technique for groundwater potential mapping at the Upper Langat Basin, Malaysia

(2011) Mohamad Abd Manap et al.   Arabian Journal of Geosciences

Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques

(2009) Alivia Chowdhury et al.   Environmental Earth Sciences

Spatial predictions of Baltic phytobenthic communities: Measuring robustness of generalized additive models based on transect data

(2008) Antonia Sandman et al.   JOURNAL OF MARINE SYSTEMS