A novel binary chaotic genetic algorithm for feature selection and its utility in affective computing and healthcare

Genetic algorithm (GA) is a nature-inspired algorithm to produce best possible solution by selecting the fittest individual from a pool of possible solutions. Like most of the optimization techniques, the GA can also stuck in the local optima, producing a suboptimal solution. This work presents a no...

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Vydané v:	Neural computing & applications Ročník 34; číslo 14; s. 11453 - 11474
Hlavní autori:	Tahir, Madiha, Tubaishat, Abdallah, Al-Obeidat, Feras, Shah, Babar, Halim, Zahid, Waqas, Muhammad
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Springer London 01.07.2022 Springer Nature B.V
Predmet:	Affective computing Artificial Intelligence Chaos theory Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Datasets Feature selection Fitness Genetic algorithms Health care Heuristic methods Image Processing and Computer Vision Optimization Optimization techniques Probability and Statistics in Computer Science S.I. : Healthcare Analytics Affective computing Feature selection Emotion identification Optimization tasks Genetic algorithms Healthcare computing
ISSN:	0941-0643, 1433-3058
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