Online probabilistic learning for fuzzy inference system

Online probabilistic learning for fuzzy inference system

Online learning is a key methodology for expert systems to gracefully cope with dynamic environments. In the context of neuro-fuzzy systems, research efforts have been directed toward developing online learning methods that can update both system structure and parameters on the fly. However, the cur...

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Bibliographic Details
Main Authors: OENTARYO, Richard Jayadi, ER, Meng Joo, LINN, San, LI, Xiang
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2014
Subjects:
Adaptive resonance theory
Bayes' rule
Kalman filter
Neuro-fuzzy system
Online learning
Databases and Information Systems
Numerical Analysis and Scientific Computing
Online Access:https://ink.library.smu.edu.sg/sis_research/3250
https://ink.library.smu.edu.sg/context/sis_research/article/4252/viewcontent/Online_probabilistic_learning_for_fuzzy_inference_pv.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/3250
https://ink.library.smu.edu.sg/context/sis_research/article/4252/viewcontent/Online_probabilistic_learning_for_fuzzy_inference_pv.pdf

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