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Advances in nature-inspired metaheuristic optimization for feature selection problem: A comprehensive survey
The main objective of feature selection is to improve learning performance by selecting
concise and informative feature subsets, which presents a challenging task for machine …
concise and informative feature subsets, which presents a challenging task for machine …
[HTML][HTML] Recent advances in harris hawks optimization: A comparative study and applications
The Harris hawk optimizer is a recent population-based metaheuristics algorithm that
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …
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 …
Harris hawks optimization algorithm: variants and applications
This paper introduces a comprehensive survey of a new swarm intelligence optimization
algorithm so-called Harris hawks optimization (HHO) and analyzes its major features. HHO …
algorithm so-called Harris hawks optimization (HHO) and analyzes its major features. HHO …
Backpropagation Neural Network optimization and software defect estimation modelling using a hybrid Salp Swarm optimizer-based Simulated Annealing Algorithm
Abstract Software Defect Estimation (SDE) is a fundamental problem solving mechanism in
the field of software engineering (SE). SDE is a task that identifies software models that are …
the field of software engineering (SE). SDE is a task that identifies software models that are …
Boolean Particle Swarm Optimization with various Evolutionary Population Dynamics approaches for feature selection problems
In the feature selection process, reaching the best subset of features is considered a difficult
task. To deal with the complexity associated with this problem, a sophisticated and robust …
task. To deal with the complexity associated with this problem, a sophisticated and robust …
[HTML][HTML] Diagnosis of obstructive sleep apnea from ECG signals using machine learning and deep learning classifiers
Obstructive sleep apnea (OSA) is a well-known sleep ailment. OSA mostly occurs due to the
shortage of oxygen for the human body, which causes several symptoms (ie, low …
shortage of oxygen for the human body, which causes several symptoms (ie, low …
Harris hawk optimization: a survey onvariants and applications
BK Tripathy, PK Reddy Maddikunta… - Computational …, 2022 - Wiley Online Library
In this review, we intend to present a complete literature survey on the conception and
variants of the recent successful optimization algorithm, Harris Hawk optimizer (HHO), along …
variants of the recent successful optimization algorithm, Harris Hawk optimizer (HHO), along …
Boosted whale optimization algorithm with natural selection operators for software fault prediction
Software fault prediction (SFP) is a challenging process that any successful software should
go through it to make sure that all software components are free of faults. In general, soft …
go through it to make sure that all software components are free of faults. In general, soft …
Intelligent detection of false information in arabic tweets utilizing hybrid harris hawks based feature selection and machine learning models
Fake or false information on social media platforms is a significant challenge that leads to
deliberately misleading users due to the inclusion of rumors, propaganda, or deceptive …
deliberately misleading users due to the inclusion of rumors, propaganda, or deceptive …