Analysis of systems of fuzzy logic to approximate fuzzy functions
Three models of fuzzy inference are considered: fuzzy pattern, fuzzy neural networks ANFIS and NEFPROX. Shown that the network ANFIS provides high quality results approximation, but requires training large number of parameters and difficult to interpret the results. Network NEFPROX convenient when i...
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| Datum: | 2015 |
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| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | Ukrainian |
| Veröffentlicht: |
PROBLEMS IN PROGRAMMING
2015
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| Online Zugang: | https://pp.isofts.kiev.ua/index.php/ojs1/article/view/106 |
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| Назва журналу: | Problems in programming |
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Problems in programming| Zusammenfassung: | Three models of fuzzy inference are considered: fuzzy pattern, fuzzy neural networks ANFIS and NEFPROX. Shown that the network ANFIS provides high quality results approximation, but requires training large number of parameters and difficult to interpret the results. Network NEFPROX convenient when interpreting results. Fuzzy pattern provides low quality of approximation and the interpretation of results difficult. |
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