Incremental FCM Technique for Black Tea Quality Evaluation Using an Electronic Nose

Fuzzy Information and Engineering

D. Ghosh¹  N. Bhattacharyya¹  A.K. Bag²  B. Tudu³  R. Bandyopadhyay³  S. Ghosh⁴ 

[1] Centre for Development of Advanced Computing, Kolkata- 700 091, India;Department of Applied Electronics and Instrumentation Engineering, FIEM, Kolkata- 700 150, India;Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata- 700 098, India;Sensor and Actuator Division CSIR-Central Glass and Ceramic Research Institute, 196 Raja S.C. Mullick Road, Jadavpur, Kolkata- 700 032, India;

关键词: Electronic nose;    Black tea quality;    Taster scores;    Gas sensors;    Fuzzy clustering;    Incremental learning;    Fuzzy c-means;   

DOI  :  10.1016/j.fiae.2015.09.002

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown