Electronic Nose Based on FSPSO Algorithm to Recognize Vinegar

Use electronic nose to detect the feed vinegar. It is to seek a kind of fast and effective method to recognize the vinegar. FCM clustering techniques which is often used has successfully dealing with many clustering problem. This paper integrates Fuzzy c-means (FCM), the simplex method and Particle Swarm Optimization (PSO) to a new kind of clustering algorithm, referred as FSPSO algorithm. The FSPSO algorithm has very strong global and local search ability, to a great extent avoided FCM algorithm easily into the local minimum defects, at the same time also reduces the sensitivity of the FCM algorithm to the initial value to improve the quality and efficiency of clustering. In this research, we use FSPSO algorithm to make cluster for the multiple vinegar data which get from the electronic nose. And compared with the FCM, FPSO, PSO, SPSO, we find that FSPSO algorithm is a stable and suitable for data clustering analysis technology.