Recent advances in Grey Wolf Optimizer, its versions and applications
The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
DETDO: An adaptive hybrid dandelion optimizer for engineering optimization
G Hu, Y Zheng, L Abualigah, AG Hussien - Advanced Engineering …, 2023 - Elsevier
Dandelion Optimizer (DO) is a recently proposed swarm intelligence algorithm that
coincides with the process of finding the best reproduction site for dandelion seeds …
coincides with the process of finding the best reproduction site for dandelion seeds …
Classification framework for faulty-software using enhanced exploratory whale optimizer-based feature selection scheme and random forest ensemble learning
Abstract Software Fault Prediction (SFP) is an important process to detect the faulty
components of the software to detect faulty classes or faulty modules early in the software …
components of the software to detect faulty classes or faulty modules early in the software …
Improved reptile search optimization algorithm using chaotic map and simulated annealing for feature selection in medical field
The increased volume of medical datasets has produced high dimensional features,
negatively affecting machine learning (ML) classifiers. In ML, the feature selection process is …
negatively affecting machine learning (ML) classifiers. In ML, the feature selection process is …
An efficient hybrid mine blast algorithm for tackling software fault prediction problem
An inherent problem in software engineering is that competing prediction systems have
been found to produce conflicting results. Yet accurate prediction is crucial because the …
been found to produce conflicting results. Yet accurate prediction is crucial because the …
Hybrid black widow optimization with iterated greedy algorithm for gene selection problems
Gene Selection (GS) is a strategy method targeted at reducing redundancy, limited
expressiveness, and low informativeness in gene expression datasets obtained by DNA …
expressiveness, and low informativeness in gene expression datasets obtained by DNA …
An efficient convergence-boosted salp swarm optimizer-based artificial neural network for the development of software fault prediction models
Abstract Machine learning (ML) approaches were employed to tackle the software fault
prediction (SFP) issue due to their consistent and rigorous performance. Multilayer …
prediction (SFP) issue due to their consistent and rigorous performance. Multilayer …
An enhanced salp swarm optimizer boosted by local search algorithm for modelling prediction problems in software engineering
Scientific communities are still motivated to create novel approaches and methodologies for
early estimation of software project development efforts and testing efforts in soft computing …
early estimation of software project development efforts and testing efforts in soft computing …
Feedforward neural network-based augmented salp swarm optimizer for accurate software development cost forecasting
This research proposes the use of feed-forward backpropagation neural networks (FFNN) to
develop an accurate cost forecasting model in light of the challenges associated with …
develop an accurate cost forecasting model in light of the challenges associated with …
Test case minimization with quantum annealers
Quantum annealers are specialized quantum computers for solving combinatorial
optimization problems with special quantum computing characteristics, eg, superposition …
optimization problems with special quantum computing characteristics, eg, superposition …