Machine learning in agriculture: A comprehensive updated review
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …
artificial intelligent systems for the sake of making value from the ever-increasing data …
Current status and future challenges of groundwater vulnerability assessment: A bibliometric analysis
Groundwater is the main source of drinking and irrigation on earth because of its large
quantity and worldly distribution, albeit unequally. However, it is presently being threatened …
quantity and worldly distribution, albeit unequally. However, it is presently being threatened …
[HTML][HTML] Optimizing durability assessment: Machine learning models for depth of wear of environmentally-friendly concrete
The use of fly ash in cementitious composites has gained popularity. However, assessing
the depth of wear (DW) of concrete requires expensive and destructive laboratory tests …
the depth of wear (DW) of concrete requires expensive and destructive laboratory tests …
Novel ensemble machine learning models in flood susceptibility mapping
The research aims to propose the new ensemble models by combining the machine
learning techniques, such as rotation forest (RF), nearest shrunken centroids (NSC), k …
learning techniques, such as rotation forest (RF), nearest shrunken centroids (NSC), k …
[HTML][HTML] Comparative study of machine learning models for evaluating groundwater vulnerability to nitrate contamination
The accurate evaluation of groundwater contamination vulnerability is essential for the
management and prevention of groundwater contamination in the watershed. In this study …
management and prevention of groundwater contamination in the watershed. In this study …
River water salinity prediction using hybrid machine learning models
Electrical conductivity (EC), one of the most widely used indices for water quality
assessment, has been applied to predict the salinity of the Babol-Rood River, the greatest …
assessment, has been applied to predict the salinity of the Babol-Rood River, the greatest …
[HTML][HTML] Prediction of sustainable concrete utilizing rice husk ash (RHA) as supplementary cementitious material (SCM): Optimization and hyper-tuning
Rice Husk ash (RHA) utilization in concrete as a waste material can contribute to the
formation of a robust cementitious matrix with utmost properties. The strength of HPC when …
formation of a robust cementitious matrix with utmost properties. The strength of HPC when …
Computational assessment of groundwater salinity distribution within coastal multi-aquifers of Bangladesh
The rising salinity trend in the country's coastal groundwater has reached an alarming rate
due to unplanned use of groundwater in agriculture and seawater seeping into the …
due to unplanned use of groundwater in agriculture and seawater seeping into the …
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 …
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
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 …
the input parameters and training dataset, but also on whether an ensemble or individual …