Fuzzy c-means based support vector machines classifier for perfume recognition

• Detection of perfumes by using machine learning algorithms.
• Fuzzy clustering c-mean: type-1 (FCM).
• Support vector machines (SVM).
• Soft computing techniques.
• Electronic (or artificial) nose.

Identification of more than three perfumes is very difficult for the human nose. It is also a problem to recognize patterns of perfume odor with an electronic nose that has multiple sensors. For this reason, a new hybrid classifier has been presented to identify type of perfume from a closely similar data set of 20 different odors of perfumes. The structure of this hybrid technique is the combination of unsupervised fuzzy clustering c-mean (FCM) and supervised support vector machine (SVM). On the other hand this proposed soft computing technique was compared with the other well-known learning algorithms. The results show that the proposed hybrid algorithm’s accuracy is 97.5% better than the others.

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