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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hell, M. Costa, P. Gomide, F. |
| Copyright Year | 2007 |
| Description | Author affiliation: Campinas State Univ., Campinas (Hell, M.; Gomide, F.) |
| Abstract | In this paper we introduce a new approach to train neurofuzzy networks using the participatory learning concept. The participatory learning paradigm tends to emulate the human learning mechanism where an acceptance mechanism determines which observation is used for learning based upon their compatibility with the current beliefs. The performance of the proposed learning scheme is illustrated by an example involving a nonlinear system modeling problem: the thermal modeling of power transformers. Comparisons with other methods reported in the literature and between two dual network structures are also included. The experimental results show the effectiveness of participatory learning in neurofuzzy networks training. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 1668300 |
| Page Count | 6 |
| File Format | |
| ISBN | 1424412099 |
| ISSN | 10987584 |
| DOI | 10.1109/FUZZY.2007.4295664 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-07-23 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Power system modeling Fuzzy systems Power transformers Training data Humans Nonlinear systems Neural networks Fuzzy sets Power engineering computing Power engineering and energy |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Artificial Intelligence Theoretical Computer Science Software |
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