Incremental FCM Technique for Black Tea Quality Evaluation Using an Electronic Nose
A novel incremental algorithm based on fuzzy-c-means (FCM) method is proposed and implemented to effectively cluster data obtained from an electronic nose for black tea quality evaluation. The algorithm segregates data generated with the electronic nose from different batches of black tea into clust...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2015-09-01
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| Series: | Fuzzy Information and Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S161686581500062X |
| _version_ | 1797708147978141696 |
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| author | B. Tudu S. Ghosh A.K. Bag D. Ghosh N. Bhattacharyya R. Bandyopadhyay |
| author_facet | B. Tudu S. Ghosh A.K. Bag D. Ghosh N. Bhattacharyya R. Bandyopadhyay |
| author_sort | B. Tudu |
| collection | DOAJ |
| description | A novel incremental algorithm based on fuzzy-c-means (FCM) method is proposed and implemented to effectively cluster data obtained from an electronic nose for black tea quality evaluation. The algorithm segregates data generated with the electronic nose from different batches of black tea into clusters with similar features, without requiring to access previously collected data. This feature of appending information exclusively from fresh data points entitles the algorithm to overcome catastrophic interference phenomenon common to conventional pattern recognition techniques. |
| first_indexed | 2024-03-12T06:18:04Z |
| format | Article |
| id | doaj.art-cf8ea844a83145d490d2b9284361326b |
| institution | Directory Open Access Journal |
| issn | 1616-8658 |
| language | English |
| last_indexed | 2024-03-12T06:18:04Z |
| publishDate | 2015-09-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Fuzzy Information and Engineering |
| spelling | doaj.art-cf8ea844a83145d490d2b9284361326b2023-09-03T02:27:16ZengTsinghua University PressFuzzy Information and Engineering1616-86582015-09-017327528910.1016/j.fiae.2015.09.002Incremental FCM Technique for Black Tea Quality Evaluation Using an Electronic NoseB. Tudu0S. Ghosh1A.K. Bag2D. Ghosh3N. Bhattacharyya4R. Bandyopadhyay5Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata- 700 098, IndiaSensor and Actuator Division CSIR-Central Glass and Ceramic Research Institute, 196 Raja S.C. Mullick Road, Jadavpur, Kolkata- 700 032, IndiaDepartment of Applied Electronics and Instrumentation Engineering, FIEM, Kolkata- 700 150, IndiaCentre for Development of Advanced Computing, Kolkata- 700 091, IndiaCentre for Development of Advanced Computing, Kolkata- 700 091, IndiaDepartment of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata- 700 098, IndiaA novel incremental algorithm based on fuzzy-c-means (FCM) method is proposed and implemented to effectively cluster data obtained from an electronic nose for black tea quality evaluation. The algorithm segregates data generated with the electronic nose from different batches of black tea into clusters with similar features, without requiring to access previously collected data. This feature of appending information exclusively from fresh data points entitles the algorithm to overcome catastrophic interference phenomenon common to conventional pattern recognition techniques.http://www.sciencedirect.com/science/article/pii/S161686581500062XElectronic noseBlack tea qualityTaster scoresGas sensorsFuzzy clusteringIncremental learningFuzzy c-means |
| spellingShingle | B. Tudu S. Ghosh A.K. Bag D. Ghosh N. Bhattacharyya R. Bandyopadhyay Incremental FCM Technique for Black Tea Quality Evaluation Using an Electronic Nose Fuzzy Information and Engineering Electronic nose Black tea quality Taster scores Gas sensors Fuzzy clustering Incremental learning Fuzzy c-means |
| title | Incremental FCM Technique for Black Tea Quality Evaluation Using an Electronic Nose |
| title_full | Incremental FCM Technique for Black Tea Quality Evaluation Using an Electronic Nose |
| title_fullStr | Incremental FCM Technique for Black Tea Quality Evaluation Using an Electronic Nose |
| title_full_unstemmed | Incremental FCM Technique for Black Tea Quality Evaluation Using an Electronic Nose |
| title_short | Incremental FCM Technique for Black Tea Quality Evaluation Using an Electronic Nose |
| title_sort | incremental fcm technique for black tea quality evaluation using an electronic nose |
| topic | Electronic nose Black tea quality Taster scores Gas sensors Fuzzy clustering Incremental learning Fuzzy c-means |
| url | http://www.sciencedirect.com/science/article/pii/S161686581500062X |
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