About: Particle Swarm Optimized Autonomous Learning Fuzzy System

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type	http://eprints.org/ontology/ArticleEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #90179 Particle Swarm Optimized Autonomous Learning Fuzzy System
sameAs	Particle Swarm Optimized Autonomous Learning Fuzzy System
Title	Particle Swarm Optimized Autonomous Learning Fuzzy System
described by	https://demo.openlinksw.com/about/id/entity/https/raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
Date	2020-02-20
Creator	Qiang Shen Plamen P. Angelov Xiaowei Gu
status	peer reviewed published
Publisher	IEEE
abstract	The antecedent and consequent parts of a first-order evolving intelligent system (EIS) determine the validity of the learning results and overall system performance. Nonetheless, the state-of-the-art techniques mostly stress on the novelty from the system identification point of view but pay less attention to the optimality of the learned parameters. Using the recently introduced autonomous learning multiple model (ALMMo) system as the implementation basis, this article introduces a particle swarm-based approach for the EIS optimization. The proposed approach is able to simultaneously optimize the antecedent and consequent parameters of ALMMo and effectively enhance the system performance by iteratively searching for optimal solutions in the problem spaces. In addition, the proposed optimization approach does not adversely influence the ``one pass'' learning ability of ALMMo. Once the optimization process is complete, ALMMo can continue to learn from new data to incorporate unseen data patterns recursively without full retraining. The experimental studies with a number of real-world benchmark problems validate the proposed concept and general principles. It is also verified that the proposed optimization approach can be applied to other types of EISs with similar operating mechanisms.
Is Part Of	IEEE Transactions on Cybernetics https://kar.kent.ac.uk/id/repository
Subject	QA 75 Electronic computers. Computer science QA 76 Software, computer programming,
list of authors	https://kar.kent.ac.uk/id/eprint/90179#authors
is topic of	https://raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #90179 Particle Swarm Optimized Autonomous Learning Fuzzy System

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