Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Rough set approach to incomplete information systems
Information Sciences: an International Journal
Rules in incomplete information systems
Information Sciences: an International Journal
Maximal consistent block technique for rule acquisition in incomplete information systems
Information Sciences: an International Journal
Mining multiple comprehensible classification rules using genetic programming
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Evolutionary granular computing model and applications
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
Culture, evolution and the puzzle of human cooperation
Cognitive Systems Research
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Analogous to biological evolution, cultural evolution also is a kind of optimal mechanism of nature. Studying this mechanism might possibly provide a more efficient computation for solving complicated problems, such as knowledge acquisition in large data set. In this paper, an algorithm, granular evolutionary algorithm for data classification, simply written as GEA, is proposed based on cultural evolution and granular computing. The proposed algorithm is essentially a granular computation, which is characterized by computing with granules. Each granule consists of some individuals, which itself also is an evolutionary population. The algorithm is realized in PVM environment by agent technology, and the experimental results certify its validity. Further analysis can find that the proposed algorithm has relatively better performance from large data sets.