Modelling and mapping of soil erosion susceptibility using machine learning in a tropical hot sub-humid environment

R Bag, I Mondal, M Dehbozorgi, SP Bank… - Journal of Cleaner …, 2022 - Elsevier
Sobha watershed, located in the Puruliya district of West Bengal, India, is experiencing
severe soil erosion due to specific geo-environmental settings and unscientific land …

A water quality prediction model based on variational mode decomposition and the least squares support vector machine optimized by the sparrow search algorithm …

C Song, L Yao, C Hua, Q Ni - Environmental monitoring and assessment, 2021 - Springer
Accurate and reliable water quality forecasting is of great significance for water resource
optimization and management. This study focuses on the prediction of water quality …

A comparison of machine learning models for suspended sediment load classification

N AlDahoul, AN Ahmed, MF Allawi… - Engineering …, 2022 - Taylor & Francis
The suspended sediment load (SSL) is one of the major hydrological processes affecting the
sustainability of river planning and management. Moreover, sediments have a significant …

Comparative assessment of individual and ensemble machine learning models for efficient analysis of river water quality

A Alqahtani, MI Shah, A Aldrees, MF Javed - Sustainability, 2022 - mdpi.com
The prediction accuracies of machine learning (ML) models may not only be dependent on
the input parameters and training dataset, but also on whether an ensemble or individual …

[HTML][HTML] Machine learning-based constitutive models for cement-grouted coal specimens under shearing

G Li, Y Sun, C Qi - International Journal of Mining Science and …, 2021 - Elsevier
Cement-based grouting has been widely used in mining engineering; its constitutive law has
not been comprehensively studied. In this study, a novel constitutive law of cement-grouted …

Comparison of self-organizing map, artificial neural network, and co-active neuro-fuzzy inference system methods in simulating groundwater quality: geospatial …

V Gholami, MR Khaleghi, S Pirasteh… - Water Resources …, 2022 - Springer
Water quality experiments are difficult, costly, and time-consuming. Therefore, different
modeling methods can be used as an alternative for these experiments. To achieve the …

Determining prone areas to gully erosion and the impact of land use change on it by using multiple-criteria decision-making algorithm in arid and semi-arid regions

M Mokarram, AR Zarei - Geoderma, 2021 - Elsevier
Gully erosion is one of the types of water erosion which causes the loss of fertile soil,
depletion of soil moisture, and so on. Due to the importance of the identification of the areas …

Snow avalanche susceptibility mapping using novel tree-based machine learning algorithms (XGBoost, NGBoost, and LightGBM) with eXplainable Artificial …

MC Iban, SS Bilgilioglu - Stochastic Environmental Research and Risk …, 2023 - Springer
This study examines the use of snow avalanche susceptibility maps (SASMs) to identify
areas prone to avalanches and develop measures to mitigate the risk in the Province of …

[HTML][HTML] Predictive analysis of cardiovascular disease using gradient boosting based learning and recursive feature elimination technique

P Theerthagiri - Intelligent Systems with Applications, 2022 - Elsevier
Background Heart disease is one of the most frequent chronic ailments people suffer. Early
identification can lower death rates by avoiding or lowering cardiovascular disease (CVD) …

Mass movement susceptibility prediction and infrastructural risk assessment (IRA) using GIS-based Meta classification algorithms

SA Ali, M Mohajane, F Parvin, A Varasano… - Applied Soft …, 2023 - Elsevier
In mountainous areas, mass movements are among the most dangerous natural hazards.
Infrastructure is a crucial component and is thought of as human wealth. This infrastructure is …