Feature selection strategy based on hybrid crow search optimization algorithm integrated with chaos theory and fuzzy c-means algorithm for medical diagnosis problems

Powerful knowledge acquisition tools and techniques have the ability to increase both the quality and the quantity of knowledge-based systems for real-world problems. In this paper, we designed a hybrid crow search optimization algorithm integrated with chaos theory and fuzzy c-means algorithm denot...

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Vydáno v:	Soft computing (Berlin, Germany) Ročník 24; číslo 3; s. 1565 - 1584
Hlavní autoři:	Anter, Ahmed M., Ali, Mumtaz
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2020 Springer Nature B.V
Témata:	Accuracy Artificial Intelligence Chaos theory Computational Intelligence Control Cost function Datasets Diagnosis Engineering Exploitation Feature selection Food Fuzzy logic Fuzzy sets Global optimization Knowledge acquisition Liver Local optimization Machine learning Mathematical Logic and Foundations Mechatronics Medical diagnosis Methodologies and Application Optimization algorithms Random variables Robotics Search algorithms Time series Feature selection Crow search optimization Medical diagnosis Chaos theory Fuzzy c-means
ISSN:	1432-7643, 1433-7479
On-line přístup:	Získat plný text
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