Water pollution examination through quality analysis of different rivers: a case study in India
Restoration of water quality at rivers is a big problem for water quality managers. This paper
analyzes water quality parameters across five years from 2012 to 2016 in a case study of …
analyzes water quality parameters across five years from 2012 to 2016 in a case study of …
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 …
groundwater potential field. According to statistics, there are three major model groups used …
Influence of data splitting on performance of machine learning models in prediction of shear strength of soil
The main objective of this study is to evaluate and compare the performance of different
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
[HTML][HTML] Flood susceptibility modelling using advanced ensemble machine learning models
ARMT Islam, S Talukdar, S Mahato, S Kundu… - Geoscience …, 2021 - Elsevier
Floods are one of nature's most destructive disasters because of the immense damage to
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
An integrated GIS, MIF, and TOPSIS approach for appraising electric vehicle charging station suitability zones in Mumbai, India
Fossil fuels cause air pollution and climate change, impacting human health. Mumbai
imports and spends heavily on petroleum. Therefore, to reduce the amount of fossil fuel and …
imports and spends heavily on petroleum. Therefore, to reduce the amount of fossil fuel and …
Groundwater level prediction using machine learning algorithms in a drought-prone area
Groundwater resources (GWR) play a crucial role in agricultural crop production, daily life,
and economic progress. Therefore, accurate prediction of groundwater (GW) level will aid in …
and economic progress. Therefore, accurate prediction of groundwater (GW) level will aid in …
Improvement of best first decision trees using bagging and dagging ensembles for flood probability mapping
Abstract Development of zoning and flood-forecasting models is essential for making
optimal management decisions before and after floods. The Komijan watershed of Markazi …
optimal management decisions before and after floods. The Komijan watershed of Markazi …
Characterization of groundwater potential zones in water-scarce hardrock regions using data driven model
The deficiency of freshwater has become a global issue in the recent era, especially in water-
scarce hard rock region including India. Groundwater (GW) as a natural resource is …
scarce hard rock region including India. Groundwater (GW) as a natural resource is …
Using machine learning models, remote sensing, and GIS to investigate the effects of changing climates and land uses on flood probability
The purpose of this study is to investigate the effects of climate and land use changes on
flood susceptibility areas in the Tajan watershed, Iran. To do this, land use changes over the …
flood susceptibility areas in the Tajan watershed, Iran. To do this, land use changes over the …
Performance evaluation of machine learning methods for forest fire modeling and prediction
Predicting and mapping fire susceptibility is a top research priority in fire-prone forests
worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB) …
worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB) …