نتایج جستجو برای: تکنیک interval fuzzy electre

تعداد نتایج: 312754  

Journal: :CoRR 2004
Haibin Wang Florentin Smarandache Yanqing Zhang Rajshekhar Sunderraman

In this paper, we present the interval neutrosophic logics which generalizes the fuzzy logic, paraconsistent logic, intuitionistic fuzzy logic and many other non-classical and non-standard logics. We will give the formal definition of interval neutrosophic propositional calculus and interval neutrosophic predicate calculus. Then we give one application of interval neutrosophic logics to do appr...

Journal: :International Mathematical Forum 2014

Journal: :Journal of Physics: Conference Series 2021

Journal: :International Journal of Computational Intelligence Systems 2012

Journal: :Honam Mathematical Journal 2010

Journal: :Journal of Korean Institute of Intelligent Systems 2012

Journal: :Inf. Sci. 2008
Zengtai Gong Bingzhen Sun Degang Chen

The notion of a rough set was originally proposed by Pawlak [Z. Pawlak, Rough sets, International Journal of Computer and Information Sciences 11 (5) (1982) 341–356]. Later on, Dubois and Prade [D. Dubois, H. Prade, Rough fuzzy sets and fuzzy rough sets, International Journal of General System 17 (2–3) (1990) 191–209] introduced rough fuzzy sets and fuzzy rough sets as a generalization of rough...

2009
Eunjin Kim Ladislav J. Kohout

This paper continues our study in fuzzy interval logic based on the Checklist Paradigm(CP) semantics of Bandler and Kohout. We investigate the fuzzy interval system of negation which was defined by the Sheffer(NAND), the Nicod(NOR) and the implication connectives of m1 interval system in depth. The top-bottom(TOPBOT) pair of fuzzy negation interval shows non-involutive property; however, it sho...

2014
Chen-Chia Chuang Jin-Tsong Jeng Sheng-Chieh Chang

Clustering algorithms have been widely used artificial intelligence, data mining and machine learning, etc. It is unsupervised classification and is divided into groups according to data sets. That is, the data sets of similarity partition belong to the same group; otherwise data sets divide other groups in the clustering algorithms. In general, to analysis interval data needs Type II fuzzy log...

Journal: :International Journal of Computer Applications 2012

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