Abstract
This paper attempts to present the new approach to design sufficient number of systematic fuzzy linguistics in matrix form and map the Fuzzy Linguistic Variable Matrix, which contains linguistic terms, into numeric domain using Fuzzy Normal Distribution based on the Parabola-based Membership Function. Existing fuzzy set theory is difficult to design the systematic and sufficient fuzzy linguistics. Due to this reason, in most practice, giving insufficient fuzzy linguistics induces inaccurate calculation whilst giving excessive fuzzy linguistics induces the parameter design problems and calculation performance. This paper presents Fuzzy Linguistic Variable Matrix and Parabola-based Fuzzy Normal Distribution (FND) as preferred framework to address the problem.
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Reference
Chen Guanrong, and Trung Tat Pham, “Introduction to fuzzy sets, fuzzy logic, and fuzzy control systems”, page 6, CRC Press, 2001
D. Dubois and H. Prade, “Possibility Theory”, Plenum Press, New York, 1988
J. C Helton, “Uncertainty and Sensitivity Analysis in the Presence of Stochastic and Subjective Uncertainty.” Journal of Statistical Computation and Simulation 57: 3–76 1997.
L.A. Zadeh, “Fuzzy Sets”, Information and Control 8(3): 338–353 1965
L.A. Zadeh, “The concept of a linguistic variable and its application to approximate reasoning — I”. Inf. Sci. 8(3): 199–249 1975
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© 2006 International Federation for Information Processing
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Yuen, K.K.F., Lau, H.G.W. (2006). Fuzzy Linguistic Variable Matrix and Parabola-Based Fuzzy Normal Distribution. In: Shi, Z., Shimohara, K., Feng, D. (eds) Intelligent Information Processing III. IIP 2006. IFIP International Federation for Information Processing, vol 228. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-44641-7_22
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DOI: https://doi.org/10.1007/978-0-387-44641-7_22
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-44639-4
Online ISBN: 978-0-387-44641-7
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