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" Frontiers of higher order fuzzy sets / "
Alireza Sadeghian, Hooman Tahayori, editors
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BL
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| Record Number
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666768
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dltt
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| Title & Author
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Frontiers of higher order fuzzy sets /\ Alireza Sadeghian, Hooman Tahayori, editors
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1 online resource
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| ISBN
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1461434416 (print)
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: 1461434424
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: 9781461434412 (print)
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: 9781461434429
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9781461434412
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| Contents
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A New Fuzzy Disjointing Difference Operator to Calculate Union and Intersection of Type-2 Fuzzy Sets -- Robustness of Higher Order Fuzzy Sets -- Fuzzy Sets of Higher Type and Higher Order in Fuzzy Modeling -- Recent Advances in Fuzzy System Modeling -- On the use of participatory genetic fuzzy system approach to develop fuzzy models -- Fuzzy Modelling of Economic Institutional Rules -- Modeling the uncertainty of a set of graphs using higher order fuzzy sets -- Time-Series Forecasting via Complex Fuzzy Logic -- Multi-Subject Type-2 Linguistic Summaries of Relational Databases -- Bio-Inspired Optimization of Interval Type-2 Fuzzy Controller Design -- Image Processing and Pattern Recognition with Interval Type-2 Fuzzy Inference Systems -- Big Data Analytic via Soft Computing Paradigms
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| Abstract
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Frontiers of Higher Order Fuzzy Sets, strives to improve the theoretical aspects of general and Interval Type-2 fuzzy sets and provides a unified representation theorem for higher order fuzzy sets. Moreover, the book elaborates on the concept of gradual elements and their integration with the higher order fuzzy sets. This book also introduces new frameworks for information granulation based on general T2FSs, IT2FSs, Gradual elements, Shadowed sets and rough sets. In particular, the properties and characteristics of the new proposed frameworks are studied. Such new frameworks are shown to be more capable to be exploited in real applications. Higher order fuzzy sets that are the result of the integration of general T2FSs, IT2FSs, gradual elements, shadowed sets and rough sets will be shown to be suitable to be applied in the fields of bioinformatics, business, management, ambient intelligence, medicine, cloud computing and smart grids. Presents new variations of fuzzy set frameworks and new areas of applicability of fuzzy theory Provides unified method for representing higher order fuzzy sets Discusses the role of gradual elements in fuzzy sets
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Artificial intelligence.
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Data structures (Computer science)
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Engineering.
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Fuzzy sets.
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Artificial Intelligence (incl. Robotics)
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Computational Intelligence.
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Data Structures, Cryptology and Information Theory.
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| Dewey Classification
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006.3
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| LC Classification
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QA248.5
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| Added Entry
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Sadeghian, Alireza
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Tahayori, Hooman
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Ohio Library and Information Network.
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