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Distances and Similarities in Intuitionistic Fuzzy Sets (Studies in Fuzziness and Soft Computing)

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This book presents the state-of-the-art in theory and practice regarding similarity and distance measures for intuitionistic fuzzy sets. Quantifying similarity and distances is crucial for many applications, e.g. data mining, machine learning, decision making, and control. The work provides readers with a comprehensive set of theoretical concepts and practical tools for both defining and determining similarity between intuitionistic fuzzy sets. It describes an automatic algorithm for deriving intuitionistic fuzzy sets from data, which can aid in the analysis of information in large databases. The book also discusses other important applications, e.g. the use of similarity measures to evaluate the extent of agreement between experts in the context of decision making.

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Fuzzy Equational Logic (Studies in Fuzziness and Soft Computing)
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Forty years have passed since the birth of fuzzy sets, in which time a wealth of theoretical developments, conceptual pursuits, algorithmic...

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This book is a tribute to Etienne E. Kerre on the occasion of his retirement on October 1st, 2010, after being active for 35 years in the field of fuzzy set theory. It gathers contributions from researchers that have been close to him in one way or another during his long and fruitful career. Besides a foreword by Lotfi A. Zadeh, it contains...


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Advances in Fuzzy Implication Functions (Studies in Fuzziness and Soft Computing)

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Keep up with the latest Office technologies, and learn the fundamentals of Microsoft Office 2016!

Office 2016 For Seniors For Dummies is the ideal resource for learning the fundamentals of the Microsoft Office suite. You'll explore the functionality of Word, Excel, PowerPoint, and Outlook, establishing basic...

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One stop guide to implementing award-winning, and cutting-edge CNN architectures

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