[HTML][HTML] An intelligent solvent selection approach in carbon capturing process: A comparative study of machine learning multi-class classification models
Carbon capture is crucial for mitigating climate change and achieving global emissions
reduction targets. Among various technologies, absorption-based methods using aqueous …
reduction targets. Among various technologies, absorption-based methods using aqueous …
[HTML][HTML] Synthetic Boosted Resampling Using Deep Generative Adversarial Networks: A Novel Approach to Improve Cancer Prediction from Imbalanced Datasets
Abstract Background/Objectives: This study examines the effectiveness of different
resampling methods and classifier models for handling imbalanced datasets, with a specific …
resampling methods and classifier models for handling imbalanced datasets, with a specific …
Machine learning based prediction of compressive and flexural strength of recycled plastic waste aggregate concrete
In the last 50 years, the use of plastics has increased significantly due to advances in
technology, population growth and increasing needs. However, this trend has led to the …
technology, population growth and increasing needs. However, this trend has led to the …
A weighted distance-based approach with boosted decision trees for label ranking
Label Ranking (LR) is an emerging non-standard supervised classification problem with
practical applications in different research fields. The Label Ranking task aims at building …
practical applications in different research fields. The Label Ranking task aims at building …
Detect, classify, and locate faults in DC microgrids based on support vector machines and bagged trees in the machine learning approach.
The DC microgrids possess numerous pros, including enhanced reliability, increased
efficiency, and a less complicated control system. Further, they provide a simplified system …
efficiency, and a less complicated control system. Further, they provide a simplified system …
Integration Sentinel-1 SAR data and machine learning for land subsidence in-depth analysis in the North Coast of Central Java, Indonesia
The escalating issue of land subsidence poses a critical threat to the economic prosperity of
Indonesia's North Coast in Central Java. This recurring phenomenon intensifies annual tidal …
Indonesia's North Coast in Central Java. This recurring phenomenon intensifies annual tidal …
Efficient ensembles of distance‐based label ranking trees
Ensemble of label ranking trees (LRTs) are currently the state‐of‐the‐art approaches to the
label ranking problem. Recently, bagging, boosting, and random forest methods have been …
label ranking problem. Recently, bagging, boosting, and random forest methods have been …
[HTML][HTML] Exploring forest fire susceptibility and management strategies in Western Himalaya: Integrating ensemble machine learning and explainable AI for accurate …
Forest fires pose a significant threat to ecosystems and socio-economic activities,
necessitating the development of accurate predictive models for effective management and …
necessitating the development of accurate predictive models for effective management and …
Discrete Beta and Shifted Beta-Binomial models for rating and ranking data
Ranking and rating methods for preference data result in a different underlying organization
of data that can lead to manifold probabilistic approaches to data modelling. As an …
of data that can lead to manifold probabilistic approaches to data modelling. As an …
Soft computing techniques to predict the compressive strength of groundnut shell ash-blended concrete
Using groundnut shell ash (GSA) as a component in concrete mixtures is a viable approach
to achieving sustainability in building practices. This particular kind of concrete has the …
to achieving sustainability in building practices. This particular kind of concrete has the …