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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Veröffentlicht in:	Soft computing (Berlin, Germany) Jg. 24; H. 3; S. 1565 - 1584
Hauptverfasser:	Anter, Ahmed M., Ali, Mumtaz
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2020 Springer Nature B.V
Schlagworte:	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
Online-Zugang:	Volltext
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