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Machine learning models for predicting compressive strength of fiber-reinforced concrete containing waste rubber and recycled aggregate
The compressive strength of fiber-reinforced rubberized recycled aggregate concrete (FR 3
C) is an important performance indicator for its practical application and durability in the …
C) is an important performance indicator for its practical application and durability in the …
[HTML][HTML] Develo** a novel tool for assessing the groundwater incorporating water quality index and machine learning approach
Groundwater plays a pivotal role as a global source of drinking water. To meet sustainable
development goals, it is crucial to consistently monitor and manage groundwater quality …
development goals, it is crucial to consistently monitor and manage groundwater quality …
[HTML][HTML] Assessing water quality of an ecologically critical urban canal incorporating machine learning approaches
This study assessed water quality (WQ) in Tongi Canal, an ecologically critical and
economically important urban canal in Bangladesh. The researchers employed the Root …
economically important urban canal in Bangladesh. The researchers employed the Root …
[HTML][HTML] Using machine learning models to estimate Escherichia coli concentration in an irrigation pond from water quality and drone-based RGB imagery data
The rapid and efficient quantification of Escherichia coli concentrations is crucial for
monitoring water quality. Remote sensing techniques and machine learning algorithms have …
monitoring water quality. Remote sensing techniques and machine learning algorithms have …
[HTML][HTML] Groundwater quality assessment and irrigation water quality index prediction using machine learning algorithms
The evaluation of groundwater quality is crucial for irrigation purposes; however, due to
financial constraints in develo** countries, such evaluations suffer from insufficient …
financial constraints in develo** countries, such evaluations suffer from insufficient …
[HTML][HTML] Improving prediction of cervical cancer using knn imputed smote features and multi-model ensemble learning approach
Simple Summary This paper presents a cervical cancer detection approach where the KNN
Imputer techniques is used to fill the missing values and after that SMOTE upsampled …
Imputer techniques is used to fill the missing values and after that SMOTE upsampled …
[HTML][HTML] Machine learning models for water quality prediction: a comprehensive analysis and uncertainty assessment in Mirpurkhas, Sindh, Pakistan
Groundwater represents a pivotal asset in conserving natural water reservoirs for potable
consumption, irrigation, and diverse industrial uses. Nevertheless, human activities …
consumption, irrigation, and diverse industrial uses. Nevertheless, human activities …
Retracted: Enhancing waste management and prediction of water quality in the sustainable urban environment using optimized algorithm of least square support …
Following an investigation into a number of papers published as part of the Urban
Groundwater Special Issue in Urban Climate, it became evident that the names of two co …
Groundwater Special Issue in Urban Climate, it became evident that the names of two co …
Improving healthcare prediction of diabetic patients using KNN imputed features and tri-ensemble model
K Alnowaiser - IEEE Access, 2024 - ieeexplore.ieee.org
Objective: Diabetes ranks as the most prevalent ailment in develo** nations. Vital steps to
mitigate the consequences of diabetes include early detection and expert medical …
mitigate the consequences of diabetes include early detection and expert medical …
Data-driven machine learning approaches for predicting slump of fiber-reinforced concrete containing waste rubber and recycled aggregate
This research investigates the slump behavior of fiber-reinforced rubberized recycled
aggregate concrete (FR 3 C) and its significance in the concrete industry. The fresh …
aggregate concrete (FR 3 C) and its significance in the concrete industry. The fresh …