Soft Computing

May 1, 2006

F-SONIA for Three-Mixture-Fragrance Recognition

Filed under: colloquium — softcomputing @ 5:04 pm

Colloquium disajikan oleh Muhammad Rahmat Widyanto, Universitas Indonesia

Resume

 A fuzzy-similarity-based self-organized network inspired by immune algorithm (F-SONIA) is proposed inorder to develop an artificialodor discriminationsystem for three-mixture-fragrance recognition. It can deal with an uncertainty in frequency measurements, which is inherent in odor acquisition devices, by employing a fuzzy similarity. Mathematical analysis shows that the use of the fuzzy similarity results on a ahigher dissimilarity between fragrance classes, therefore, the recognition accuracy is improved and the learning time is reduced. Experiments show that F-SONIA improves recognition accuracy of SONIA by 3%-9% and the previously developed artificial odor discrimination system by 14%-25%. In addition, the learning time of F-SONIA is three times faster than that of SONIA.

Referensi

Muhammad Rahmat Widyanto, Benyamin Kusumoputro, Hajime Nobuhara, Kazuhiko Kawamoto, and Kaoru Hirota, "A Fuzzy-Similarity-Based Self-Organized Network Inspired by Immune Algorithm for Three-Mixture-Fragrance Recognition", IEEE Trans. on Industrial Electronics, Vol.53, No.1, February 2006 

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