Abstract
Machine vision, hearing are greatly developed in the domain of robotics and some of them have been used for practical purposes. However, the progress made in machine taste and smell sensation is far from satisfaction. A Takagi-Sugeno (T-S) model for recognizing the taste signals of tea is proposed. In the model, a hierarchical genetic algorithm is used to extract fuzzy if-then rules, and it can obtain the near-optimal structure of T-S model for taste identification of tea. Numerical simulations show the effectiveness of the proposed algorithm.
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Ma, M., Zhang, LB., Sun, Y. (2009). Recognizing the Taste Signals of Tea Using T-S Fuzzy Model. In: Cao, B., Li, TF., Zhang, CY. (eds) Fuzzy Information and Engineering Volume 2. Advances in Intelligent and Soft Computing, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03664-4_80
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DOI: https://doi.org/10.1007/978-3-642-03664-4_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03663-7
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