Comprehensive systematic review of intelligent approaches in UAV-based intrusion detection, blockchain, and network security

AB Mohammed, LC Fourati, AM Fakhrudeen - Computer Networks, 2024‏ - Elsevier
Abstract Unmanned Aerial Vehicles (UAVs) have evolved into a pivotal component of
electronic devices deployed across a diverse array of sectors and industries in recent years …

Ensemble machine learning paradigms in software defect prediction

T Sharma, A Jatain, S Bhaskar, K Pabreja - Procedia Computer Science, 2023‏ - Elsevier
Predicting faults in software aims to detect defects before the testing phase, allowing for
better resource allocation and high-quality software development, which is a requisite for …

Multi-strategy augmented Harris Hawks optimization for feature selection

Z Zhao, H Yu, H Guo, H Chen - Journal of Computational Design …, 2024‏ - academic.oup.com
In the context of increasing data scale, contemporary optimization algorithms struggle with
cost and complexity in addressing the feature selection (FS) problem. This paper introduces …

[HTML][HTML] Software defect prediction using wrapper feature selection based on dynamic re-ranking strategy

AO Balogun, S Basri, LF Capretz, S Mahamad… - Symmetry, 2021‏ - mdpi.com
Finding defects early in a software system is a crucial task, as it creates adequate time for
fixing such defects using available resources. Strategies such as symmetric testing have …

An empirical study on data sampling methods in addressing class imbalance problem in software defect prediction

BJ Odejide, AO Bajeh, AO Balogun… - Computer Science On …, 2022‏ - Springer
With the growing rate of software systems and their applications in diverse walks of life,
develo** a software system that has no defects is a subject that cannot be …

Prior knowledge evaluation and emphasis sampling-based evolutionary algorithm for high-dimensional medical data feature selection

Z Wang, L Shao, AA Heidari, M Wang… - Expert Systems with …, 2025‏ - Elsevier
Handling high-dimensional medical data presents a significant challenge. Numerous
irrelevant and redundant features impede the construction of high-precision models …

A importance-based ensemble method using an adaptive threshold searching for feature selection

Y Zhuang, Z Fan, J Gou, Y Huang, W Feng - Expert Systems with …, 2025‏ - Elsevier
Current single feature selection algorithms have certain limitations when it comes to
effectively addressing challenges presented by various tasks and data contexts. As a result …

[HTML][HTML] Feature optimization method of material identification for loose particles inside sealed relays

Z Sun, A Jiang, G Wang, M Zhang, H Yan - Sensors, 2022‏ - mdpi.com
Existing material identification for loose particles inside sealed relays focuses on the
selection and optimization of classification algorithms, which ignores the features in the …

A Novel Rank Aggregation‐Based Hybrid Multifilter Wrapper Feature Selection Method in Software Defect Prediction

AO Balogun, S Basri, S Mahamad… - Computational …, 2021‏ - Wiley Online Library
The high dimensionality of software metric features has long been noted as a data quality
problem that affects the performance of software defect prediction (SDP) models. This …

Hybrid feature selection method for predicting software defect

AJ Anju, JE Judith - Journal of Engineering and Applied Science, 2024‏ - Springer
To address the challenges associated with the abundance of features in software datasets,
this study proposes a novel hybrid feature selection method that combines quantum particle …