[HTML][HTML] Comparison of machine learning and statistical approaches to estimate rock tensile strength
Z Fang, J Cheng, C Xu, X Xu, J Qajar… - Case Studies in …, 2024 - Elsevier
Tensile strength is very important in drilling operations. The main objective of this study was
to assess petrography, physical, and mechanical properties and predict the Brazilian tensile …
to assess petrography, physical, and mechanical properties and predict the Brazilian tensile …
A novel metaheuristic optimization and soft computing techniques for improved hydrological drought forecasting
Drought is one of the costliest natural disasters worldwide and weakens countries
economically by causing negative impacts on hydropower and agricultural production …
economically by causing negative impacts on hydropower and agricultural production …
Support vector machine (SVM) model development for prediction of fecal coliform of Upper Green River Watershed, Kentucky, USA
M Talnikar, J Anmala, T Venkateswarlu… - Sustainable Water …, 2024 - Springer
The classification and prediction of water quality parameters (WQPs) such as Fecal Coliform
in river waters are crucial for developing a Decision Support System or Tool for water quality …
in river waters are crucial for developing a Decision Support System or Tool for water quality …
[PDF][PDF] Effective Machine-Learning Models for Rock Mass Deformation Modulus Estimation Based on Rock Mass Classification Systems
The rock mass deformation modulus (RMDM) plays a crucial role in dam and tunnel design.
This study introduces advanced machine-learning (ML) models to predict RMDM using rock …
This study introduces advanced machine-learning (ML) models to predict RMDM using rock …