Machine learning in geo-and environmental sciences: From small to large scale

P Tahmasebi, S Kamrava, T Bai, M Sahimi - Advances in Water Resources, 2020 - Elsevier
In recent years significant breakthroughs in exploring big data, recognition of complex
patterns, and predicting intricate variables have been made. One efficient way of analyzing …

Global review of groundwater potential models in the last decade: parameters, model techniques, and validation

NN Thanh, P Thunyawatcharakul, NH Ngu… - Journal of …, 2022 - Elsevier
This paper aims to review parameters, model techniques, validation methods in
groundwater potential field. According to statistics, there are three major model groups used …

Spatial prediction of groundwater potential map** based on convolutional neural network (CNN) and support vector regression (SVR)

M Panahi, N Sadhasivam, HR Pourghasemi… - Journal of …, 2020 - Elsevier
Freshwater shortages have become much more common globally in recent years. Water
resources that are naturally available beneath the surface are capable of reversing this …

Delineation of groundwater potential zones in a drought-prone semi-arid region of east India using GIS and analytical hierarchical process techniques

I Mukherjee, UK Singh - Catena, 2020 - Elsevier
Over-extraction of groundwater has compromised its climatic resilience properties and the
arid/semi-arid rural tracts are becoming increasingly vulnerable to the risks of groundwater …

Regenerative agriculture and integrative permaculture for sustainable and technology driven global food production and security

E McLennon, B Dari, G Jha, D Sihi… - Agronomy …, 2021 - Wiley Online Library
A growing world population and increases in food and energy consumption have placed
production agriculture in a difficult situation. The rapid growth in food production through …

Soft computing ensemble models based on logistic regression for groundwater potential map**

PT Nguyen, DH Ha, M Avand, A Jaafari, HD Nguyen… - Applied Sciences, 2020 - mdpi.com
Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …

Assessing and map** multi-hazard risk susceptibility using a machine learning technique

HR Pourghasemi, N Kariminejad, M Amiri, M Edalat… - Scientific reports, 2020 - nature.com
The aim of the current study was to suggest a multi-hazard probability assessment in Fars
Province, Shiraz City, and its four strategic watersheds. At first, we construct maps depicting …