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書目名稱Granular Computing: At the Junction of Rough Sets and Fuzzy Sets影響因子(影響力)




書目名稱Granular Computing: At the Junction of Rough Sets and Fuzzy Sets影響因子(影響力)學(xué)科排名




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書目名稱Granular Computing: At the Junction of Rough Sets and Fuzzy Sets網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Granular Computing: At the Junction of Rough Sets and Fuzzy Sets被引頻次




書目名稱Granular Computing: At the Junction of Rough Sets and Fuzzy Sets被引頻次學(xué)科排名




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書目名稱Granular Computing: At the Junction of Rough Sets and Fuzzy Sets讀者反饋




書目名稱Granular Computing: At the Junction of Rough Sets and Fuzzy Sets讀者反饋學(xué)科排名

膽小鬼

Similarities for Crisp and Fuzzy Probabilistic Expert Systems0] such a question was discussed and a solution was proposed. In this chapter we start from the ideas in [10] to sketch a method to design expert systems, probabilistic in nature. Indeed, we assume that the probability an individual satisfies a property is the percentage of similar individuals satis

滔滔不絕的人

FLOUR

Entropy and Co–entropy of Partitions and Coverings with Applications to Roughness Theorygies generated by partitions, according to the Pawlak approach to rough set theory. In this partition context of a finite universe, typical of complete information systems, the probability space generated by the counting measure is analyzed, with particular regard to a local notion of rough entropy

Cosmopolitan

Patterns of Collaborations in Rough Set Researchts at the present time and study its evolution over the past 25 years. Our approach is more experimental and statistical rather than theoretical. It seems that these data are interesting in their own right as a reflection of the way in which the rough set research is done, apart from the mathematica

Eosinophils

Eosinophils

A Coevolutionary Approach to Solve Fuzzy Gamesthe players must find strategies to optimize their payoffs. The co-evolutionary approach suggested herein is a heuristic procedure that maintains a population of players, each of which having a particular strategy. Both, zero and nonzero sum games are solved by the coevolutionary procedure. Contrary

顯而易見

jeopardize

Learning Membership Functions for an Associative Fuzzy Neural Network way to model linear attributes as linguistic variables. The utilization of such functions in five different fashions in the context of an Associative Fuzzy Neural Network outperformed two existing methods. Also, these heuristic methods are suitable for being applied to other knowledge representatio

懶惰人民