An Approach for Online Weight Update Using Particle Swarm Optimization in Dynamic Fuzzy Cognitive Maps

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dc.contributor.authorAltundogan T.G.
dc.contributor.authorKarakose M.
dc.date.accessioned2024-07-22T08:09:27Z
dc.date.available2024-07-22T08:09:27Z
dc.date.issued2018
dc.description.abstractFuzzy cognitive maps (FCM) is a method to update a given initial vector to obtain the most stable state of a system, using a neighborhood of weights between these vectors and updating it over a series of iterations. FCMs are modeled with graphs. Neighbor weights between nodes are between-1 and 1. Nowadays it is used in business management, information technology, communication, health and medical decision making, engineering and computer vision. In this study, a dynamic FCM structure based on Particle Swarm Optimization (PSO) is given for determining node weights and online updating for modeling of dynamic systems with FCMs. Neighborhood weights in dynamic FCMs can be updated instantly and the system feedback is used for this update. In this work, updating the weights of the dynamic FCM is a PSO based approach that takes advantage of system feedback. In previous literature suggestions, dynamic FCM structure performs the weight updating process by using rule-based methods such as Hebbian. Metaheuristic methods are less complex and more efficient than rule-based methods in such optimization problems. In the developed PSO approach, the initialize vector state of the system, the weights between the vector nodes, and the desired steady state vector are taken into consideration. As a fitness function, the system has benefited from the convergence state to the desired steady state vector. As a stopping criterion for PSO, 100 ∗ n number of iteration limits have been applied for the initial vector with n nodes. The proposed method has been tested for five different scenarios with different node counts. © 2018 IEEE.
dc.identifier.DOI-ID10.1109/UBMK.2018.8566363
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/14827
dc.language.isoEnglish
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectCognitive systems
dc.subjectDecision making
dc.subjectFuzzy rules
dc.subjectIterative methods
dc.subjectLarge scale systems
dc.subjectOnline systems
dc.subjectVectors
dc.subjectDynamic maps
dc.subjectFuzzy cognitive map
dc.subjectMedical decision making
dc.subjectMeta-heuristic methods
dc.subjectModeling of dynamics
dc.subjectNumber of iterations
dc.subjectOptimization problems
dc.subjectWeight update
dc.subjectParticle swarm optimization (PSO)
dc.titleAn Approach for Online Weight Update Using Particle Swarm Optimization in Dynamic Fuzzy Cognitive Maps
dc.typeConference paper

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