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] Developing 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 …
Enhancing waste management and prediction of water quality in the sustainable urban environment using optimized algorithm of least square support vector machine …
Urban groundwater influences a wide range of processes in the natural world, including
climatic, geological, geomorphic, biogeochemical, ecotoxicological, hydrological, and …
climatic, geological, geomorphic, biogeochemical, ecotoxicological, hydrological, and …
[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 …
Combining CNN features with voting classifiers for optimizing performance of brain tumor classification
Simple Summary This study presents a hybrid model for brain tumor detection. Contrary to
manual featur extraction, features extracted from a convolutional neural network are used to …
manual featur extraction, features extracted from a convolutional neural network are used to …
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 …
Imputer techniques is used to fill the missing values and after that SMOTE upsampled …
[HTML][HTML] Machine Learning Algorithms for Water Quality Management Using Total Dissolved Solids (TDS) Data Analysis
Our research project specifically focuses on evaluating groundwater quality in six West
Texas counties. We aim to determine whether environmental changes have any impact on …
Texas counties. We aim to determine whether environmental changes have any impact on …
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 …
A novel approach for breast cancer detection using optimized ensemble learning framework and XAI
Breast cancer (BC) is a common and highly lethal ailment. It stands as the second leading
contributor to cancer-related deaths in women worldwide. The timely identification of this …
contributor to cancer-related deaths in women worldwide. The timely identification of this …
Improving prediction of blood cancer using leukemia microarray gene data and Chi2 features with weighted convolutional neural network
Blood cancer has emerged as a growing concern over the past decade, necessitating early
diagnosis for timely and effective treatment. The present diagnostic method, which involves …
diagnosis for timely and effective treatment. The present diagnostic method, which involves …