Neutrosophic multi-criteria decision making / / special issue editors, Florentin Smarandache, Jun Ye, Yanhui Guo

• Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2018
• Descrizione fisica: 1 electronic resource (206 p.)
• Soggetto topico: Artificial intelligence; Computer science
• Soggetto non controllato: Neutrosophic optimization; Neutrosophic medical diagnosis; Neutrosophic data mining; Neutrosophic operations used in MCDM; NMCD Neutrosophic applications; Neutrosophic fault diagnosis; Neutrosophic computational modelling; Neutrosophic image processing using MCDM; Neutrosophic clustering analysis; Neutrosophic decision making theories and methods
• Persona (resp. second.): GuoYanhui; SmarandacheFlorentin; YeJun <1967->
• Sommario/riassunto: Neutrosophic logic and set are gaining significant attention in solving many real-life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistency, and indeterminacy. A number of new neutrosophic theories have been proposed and have been applied in Multi-Criteria Decision-Making, computational intelligence, multiple-attribute decision-making, image processing, medical diagnosis, fault diagnosis, optimization design, and so on. Neutrosophic logic, set, probability, statistics, etc., are, respectively, generalizations of fuzzy and intuitionistic fuzzy logic and set, classical and imprecise probability, classical statistics and so on. This Special Issue gathers 11 original research papers that report on the state of the art and recent advancements in Multi-Criteria Decision-Making using neutrosophic environment in computing, artificial intelligence, big and small data mining, group decision-making problems, pattern recognition, information processing, image processing, and many other practical achievements.
• Titolo autorizzato: Neutrosophic Multi-Criteria Decision Making
• ISBN: 3-03897-289-4; 3-03897-288-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910346680103321
• Lo trovi qui: Univ. Federico II