Metaheuristic algorithms on feature selection: A survey of one decade of research (2009-2019)
Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …
dimension of the feature set while maintaining the accuracy of the performance is the main …
Software defect prediction using ensemble learning: A systematic literature review
Recent advances in the domain of software defect prediction (SDP) include the integration of
multiple classification techniques to create an ensemble or hybrid approach. This technique …
multiple classification techniques to create an ensemble or hybrid approach. This technique …
Outlook on human-centric manufacturing towards Industry 5.0
The recent shift to wellbeing, sustainability, and resilience under Industry 5.0 has prompted
formal discussions that manufacturing should be human-centric–placing the wellbeing of …
formal discussions that manufacturing should be human-centric–placing the wellbeing of …
Review of swarm intelligence-based feature selection methods
In the past decades, the rapid growth of computer and database technologies has led to the
rapid growth of large-scale datasets. On the other hand, data mining applications with high …
rapid growth of large-scale datasets. On the other hand, data mining applications with high …
Integrated structural health monitoring in bridge engineering
Integrated structural health monitoring (SHM) uses the mechanism analysis, monitoring
technology and data analytics to diagnose the classification, location and significance of …
technology and data analytics to diagnose the classification, location and significance of …
Multiclass feature selection with metaheuristic optimization algorithms: a review
Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …
selection is harder to perform since most classifications are binary. The feature selection …
A review of android malware detection approaches based on machine learning
K Liu, S Xu, G Xu, M Zhang, D Sun, H Liu - IEEE access, 2020 - ieeexplore.ieee.org
Android applications are developing rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …
malware is also emerging in an endless stream. Many researchers have studied the …
Comprehensive review of artificial neural network applications to pattern recognition
The era of artificial neural network (ANN) began with a simplified application in many fields
and remarkable success in pattern recognition (PR) even in manufacturing industries …
and remarkable success in pattern recognition (PR) even in manufacturing industries …
A hybrid intelligent system framework for the prediction of heart disease using machine learning algorithms
Heart disease is one of the most critical human diseases in the world and affects human life
very badly. In heart disease, the heart is unable to push the required amount of blood to …
very badly. In heart disease, the heart is unable to push the required amount of blood to …