Machine learning models for predicting compressive strength of fiber-reinforced concrete containing waste rubber and recycled aggregate

A Pal, KS Ahmed, FMZ Hossain, MS Alam - Journal of Cleaner Production, 2023 - Elsevier
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 …

[HTML][HTML] Develo** a novel tool for assessing the groundwater incorporating water quality index and machine learning approach

AM Sajib, MTM Diganta, A Rahman… - Groundwater for …, 2023 - Elsevier
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 …

[HTML][HTML] Assessing water quality of an ecologically critical urban canal incorporating machine learning approaches

AM Sajib, MTM Diganta, M Moniruzzaman… - Ecological …, 2024 - Elsevier
This study assessed water quality (WQ) in Tongi Canal, an ecologically critical and
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

SM Hong, BJ Morgan, MD Stocker, JE Smith, MS Kim… - Water research, 2024 - Elsevier
The rapid and efficient quantification of Escherichia coli concentrations is crucial for
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

EE Hussein, A Derdour, B Zerouali, A Almaliki… - Water, 2024 - mdpi.com
The evaluation of groundwater quality is crucial for irrigation purposes; however, due to
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

H Karamti, R Alharthi, AA Anizi, RM Alhebshi… - Cancers, 2023 - mdpi.com
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 …

[HTML][HTML] Machine learning models for water quality prediction: a comprehensive analysis and uncertainty assessment in Mirpurkhas, Sindh, Pakistan

F Abbas, Z Cai, M Shoaib, J Iqbal, M Ismail, AF Alrefaei… - Water, 2024 - mdpi.com
Groundwater represents a pivotal asset in conserving natural water reservoirs for potable
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 …

S Zhang, AH Omar, AS Hashim, T Alam, HAEW Khalifa… - 2023 - Elsevier
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 …

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 …

Data-driven machine learning approaches for predicting slump of fiber-reinforced concrete containing waste rubber and recycled aggregate

A Pal, KS Ahmed, S Mangalathu - Construction and Building Materials, 2024 - Elsevier
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 …