CALA-FOMF: a continuous action-set learning automata-based approach to finding optimized membership functions for fuzzy association rules in web usage data-Reference-Cited by-同舟云学术

CALA-FOMF: a continuous action-set learning automata-based approach to finding optimized membership functions for fuzzy association rules in web usage data

Published:2020-06-04 Issue:23 Volume:24 Page:18089-18112
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Anari Zohreh,Hatamlou Abdolreza^ORCID,Masdari Mohammad

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-020-05064-7.pdf

Reference75 articles.

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3. Alcalá-Fdez J, Alcalá R, Gacto MJ, Herrera F (2009) Learning the membership function contexts for mining fuzzy association rules by using genetic algorithms. Fuzzy Sets Syst 160(7):905–921

4. Alikhademi F, Zainudin S (2014) Generating of derivative membership functions for fuzzy association rule mining by Particle Swarm Optimization. Paper presented at the 2014 international conference on computational science and technology (ICCST)

5. Anari B, Torkestani JA, Rahmani AM (2017) Automatic data clustering using continuous action-set learning automata and its application in segmentation of images. Appl Soft Comput 51:253–265

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