Adaptive fuzzy rule-based classification system integrating both expert knowledge and data
This paper presents an adaptive fuzzy rule-based classification system using a new hybrid modeling method that integrates both expert knowledge and new knowledge learnt from data. Inspired by human learning, the membership functions of fuzzy rules are optimized based on a hybrid error function that...
Main Authors: | Ng, Gee Wah, Tang, Wenyin, Mao, Kezhi, Mak, Lee Onn |
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Other Authors: | School of Electrical and Electronic Engineering |
Format: | Conference Paper |
Language: | English |
Published: |
2013
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/99301 http://hdl.handle.net/10220/12873 |
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