Abstract
In this paper we provide the restructuring method of rough sets for analyzing fuzzy random data that many experts evaluate creative cities. Usually it is hard to clarify the situation where randomness and fuzziness exist simultaneously. This paper presents a method based on fuzzy random variables to restructure a rough set. The algorithms of rough set is used to distinguish whether a subset can be classified in the object set or not based on confidence interval. The expected-value-approach is also applied to calculate the fuzzy value with probability into a scalar value.
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Lin, LC., Watada, J. (2010). Restructuring of Rough Sets for Fuzzy Random Data of Creative City Evaluation. In: Huynh, VN., Nakamori, Y., Lawry, J., Inuiguchi, M. (eds) Integrated Uncertainty Management and Applications. Advances in Intelligent and Soft Computing, vol 68. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11960-6_48
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DOI: https://doi.org/10.1007/978-3-642-11960-6_48
Publisher Name: Springer, Berlin, Heidelberg
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