4.7 Article

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

Related references

Note: Only part of the references are listed.
Article Geosciences, Multidisciplinary

Groundwater potential mapping using a novel data-mining ensemble model

Mojtaba Dolat Kordestani et al.

HYDROGEOLOGY JOURNAL (2019)

Article Energy & Fuels

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

Shuhua Wang et al.

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2019)

Article Engineering, Civil

Mapping Groundwater Potential Using a Novel Hybrid Intelligence Approach

Shaghayegh Miraki et al.

WATER RESOURCES MANAGEMENT (2019)

Article Geosciences, Multidisciplinary

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

Maher Ibrahim Sameen et al.

NATURAL RESOURCES RESEARCH (2019)

Article Geosciences, Multidisciplinary

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

G. Gnanachandrasamy et al.

JOURNAL OF THE GEOLOGICAL SOCIETY OF INDIA (2018)

Proceedings Paper Mathematics, Applied

Aquifer Characterization and Groundwater Potential Evaluation in Sedimentary Rock Formation

M. A. M. Ashraf et al.

INTERNATIONAL SEMINAR ON MATHEMATICS AND PHYSICS IN SCIENCES AND TECHNOLOGY 2017 (ISMAP 2017) (2018)

Article Computer Science, Interdisciplinary Applications

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

Benjamin Hofner et al.

JOURNAL OF STATISTICAL SOFTWARE (2016)

Article Engineering, Multidisciplinary

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

Huajie Duan et al.

MATHEMATICAL PROBLEMS IN ENGINEERING (2016)

Article Environmental Sciences

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

Alaa M. Al-Abadi et al.

ENVIRONMENTAL MONITORING AND ASSESSMENT (2015)

Article Geosciences, Multidisciplinary

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

Mohamad Abd Manap et al.

ARABIAN JOURNAL OF GEOSCIENCES (2013)

Article Statistics & Probability

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

Andreas Mayr et al.

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS (2012)

Article Environmental Sciences

Deciphering potential groundwater zone in hard rock through the application of GIS

R. K. Prasad et al.

ENVIRONMENTAL GEOLOGY (2008)

Article Business

Bagging and boosting classification trees to predict churn

A Lemmens et al.

JOURNAL OF MARKETING RESEARCH (2006)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)