Soft Computing: State of the Art Theory and Novel - download pdf or read online

By Ali M. Abbasov (auth.), Ronald R. Yager, Ali M. Abbasov, Marek Z. Reformat, Shahnaz N. Shahbazova (eds.)

ISBN-10: 3642349218

ISBN-13: 9783642349218

ISBN-10: 3642349226

ISBN-13: 9783642349225

This booklet is a tribute to Lotfi A. Zadeh, the daddy of fuzzy good judgment, at the celebration of his 90th Birthday. The publication gathers unique clinical contributions written by way of best scientists and providing the newest theories, purposes and new tendencies within the attention-grabbing and hard box of soppy computing.

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Extra resources for Soft Computing: State of the Art Theory and Novel Applications

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13) Compute the coverage of each solution. Coverage provides a measure of generality of a summary because it shows how many cases support the summary. It is an assessment of the degree to which a solution is supported by cases. In other words, coverage determines what percentage of cases covers a solution. Ragin [20, Ch. 3] mentions three kinds of coverage and Rihoux and Ragin [23, p. 64] define them as: (1) solution coverage, Cs, which is the proportion of cases that are covered by all of the terms; (2) raw coverage, Cr, which is the proportion of cases that are simultaneously covered by each term one at a time; and, (3) unique coverage, Cu, which is the proportion of cases that are uniquely covered by a specific term (no other terms cover those cases).

Frawley, B. ) Knowledge Discovery in Databases, pp. 347–363. : Linguistic summaries as a tool for database discovery. In: Proc. FUZZIEEE 1995/IFES 1995, Yokohama, Japan, pp. : Database discovery using fuzzy sets. International Journal of Intelligent Systems 11, 691–712 (1996) The Kendall Rank Correlation between Intuitionistic Fuzzy Sets: An Extended Analysis Eulalia Szmidt1,2 , Janusz Kacprzyk1,2, and Paweł Bujnowski1 1 2 Systems Research Institute, Polish Academy of Sciences, ul. pl WIT – Warsaw School of Information Technology ul.

Szmidt, J. Kacprzyk, and P. Bujnowski Table 5. 62 petal width 1 Table 6. 7 petal width 1 Table 7. 61 petal width 1 Table 8. 64 petal width 1 Table 9. 86 petal width 1 The Kendall Rank Correlation between Intuitionistic Fuzzy Sets 51 Table 10. 89 petal width 1 Table 11. 61 petal width 1 Table 12. 78 petal width 1 Table 13. 76 petal width 1 The Kendall correlation coefficient (15) – Table 4 is the biggest between petal length and petal width, and does not count only between sepal length and sepal width.

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Soft Computing: State of the Art Theory and Novel Applications by Ali M. Abbasov (auth.), Ronald R. Yager, Ali M. Abbasov, Marek Z. Reformat, Shahnaz N. Shahbazova (eds.)


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