Abstract
It plays an important role in sensory evaluation to optimize experiment design, i.e. using less number of tests to obtain available data as possible by intelligent technologies. This paper presents one method for optimizing experiment design based on learning automaton, and this method is applied in computer aided sensory evaluation (abbr. CASE). The validity of this method is showed by the result of experiment from CASE.
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References
Dijksterhuis, G.B.: Multivariate data analysis in sensory and consumer science. Food & nutrition press, Trumbull (1997)
Zeng, X.Y., Ding, Y.S.: An introduction to intelligent evaluation. Journal of Donghua university 3, 1–4 (2004)
Goer, J.C.: Generalized Procrustes Analysis. Psychometrika 40, 33–51 (1975)
Van der Burg, E.: Nonlinear canonical correlation and some related techniques. DSWO press, Leiden (1988)
Van der Burg, E., Dijksterhuis, D.B.: Nonlinear canonical Correlation Analysis of Multiway Data. In: Coppi, R., Bolasco, S. (eds.) Multiway Data Analysis, pp. 245–255. Elsevier Science Publisher B.V, Amsterdam (1989)
Stone, H., Sidel, J.L.: Sensory Evaluation Practices, 3rd edn. Academic Press, San Diego (2004)
Lewandowsky, S., Murdock, B.B.: Memory for serial order. Psychological Review 96, 25–57 (1989)
Lakshmivarahan, S.: Learning algorithms theory and applications. Springer, New York (1981)
Zeng, X.Y., Liu, Z.Y.: A learning automata based algorithm for optimization of Continuous Complex Functions. Information science 174(Issue 3-4), 165–175 (2005)
Liu, X.H., et al.: A method for optimizing dichotomy in sensory evaluation. In: 2006 International Conference on Intelligent Systems & Knowledge Engineering (ISKE2006), Shanghai, China, April 6-7 (2006)
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© 2007 Springer-Verlag Berlin Heidelberg
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Luo, B. (2007). A Dynamic Method of Experiment Design of Computer Aided Sensory Evaluation. In: Melin, P., Castillo, O., Ramírez, E.G., Kacprzyk, J., Pedrycz, W. (eds) Analysis and Design of Intelligent Systems using Soft Computing Techniques. Advances in Soft Computing, vol 41. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72432-2_51
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DOI: https://doi.org/10.1007/978-3-540-72432-2_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72431-5
Online ISBN: 978-3-540-72432-2
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