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Uncertainty Data in Interval-Valued Fuzzy Set Theory, Barbara P?kala


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Автор: Barbara P?kala
Название:  Uncertainty Data in Interval-Valued Fuzzy Set Theory
ISBN: 9783030067434
Издательство: Springer
Классификация:


ISBN-10: 3030067432
Обложка/Формат: Soft cover
Страницы: 181
Вес: 0.31 кг.
Дата издания: 2019
Серия: Studies in Fuzziness and Soft Computing
Язык: English
Иллюстрации: XIV, 181 p. 12 illus.
Размер: Book (Paperback Initiative)
Основная тема: Engineering
Подзаголовок: Properties, Algorithms and Applications
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov’s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data.
Дополнительное описание: Introduction to Fuzzy Sets.- Interval-Valued Fuzzy Relations.- Applications.- Summary and Open Problem.



Knowledge Processing with Interval and Soft Computing

Автор: Chenyi Hu; R. Baker Kearfott; Andre de Korvin; Vla
Название: Knowledge Processing with Interval and Soft Computing
ISBN: 1849967849 ISBN-13(EAN): 9781849967846
Издательство: Springer
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Цена: 19564.00 р.
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Описание: Interval computing combined with fuzzy logic is an emerging tool in studying artificial intelligence and knowledge processing (AIKP) applications. This accessible book, a must-read for those in AI, provides introductions for both interval and fuzzy computing.

Interval-Valued Intuitionistic Fuzzy Sets

Автор: Krassimir T. Atanassov
Название: Interval-Valued Intuitionistic Fuzzy Sets
ISBN: 3030320898 ISBN-13(EAN): 9783030320898
Издательство: Springer
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Цена: 13974.00 р.
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Описание: The book offers a comprehensive survey of interval-valued intuitionistic fuzzy sets.

Models and Methods for Interval-Valued Cooperative Games in Economic Management

Автор: Deng-Feng Li
Название: Models and Methods for Interval-Valued Cooperative Games in Economic Management
ISBN: 3319289969 ISBN-13(EAN): 9783319289960
Издательство: Springer
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Цена: 11179.00 р.
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Описание: This book proposes several commonly used interval-valued solution concepts of interval-valued cooperative games with transferable utility.

Computing Statistics under Interval and Fuzzy Uncertainty

Автор: Hung T. Nguyen; Vladik Kreinovich; Berlin Wu; Gang
Название: Computing Statistics under Interval and Fuzzy Uncertainty
ISBN: 3642445705 ISBN-13(EAN): 9783642445705
Издательство: Springer
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Цена: 23508.00 р.
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Описание: if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1.

Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion

Автор: Christian Servin; Vladik Kreinovich
Название: Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion
ISBN: 3319385879 ISBN-13(EAN): 9783319385877
Издательство: Springer
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Цена: 13059.00 р.
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Описание: On various examples ranging from geosciences to environmental sciences, thisbook explains how to generate an adequate description of uncertainty, how to justifysemiheuristic algorithms for processing uncertainty, and how to make these algorithmsmore computationally efficient.

Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications

Автор: Andrew Pownuk; Vladik Kreinovich
Название: Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications
ISBN: 3030081583 ISBN-13(EAN): 9783030081584
Издательство: Springer
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Цена: 16769.00 р.
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Описание:

How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc.
In all these developments, the authors’ objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty.
The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty.
How Interval and Fuzzy Techniques Can Improve Teaching

Автор: Olga Kosheleva; Karen Villaverde
Название: How Interval and Fuzzy Techniques Can Improve Teaching
ISBN: 3662572567 ISBN-13(EAN): 9783662572566
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book explains how to teach better and presents the latest research on processing educational data and presents traditional statistical techniques as well as probabilistic, interval, and fuzzy approaches. Teaching is a very rewarding activity; it is also a very difficult one – because it is largely an art. There is a lot of advice on teaching available, but it is usually informal and is not easy to follow. To remedy this situation, it is reasonable to use techniques specifically designed to handle such imprecise knowledge: the fuzzy logic techniques. Since there are a large number of statistical studies of different teaching techniques, the authors combined statistical and fuzzy approaches to process the educational data in order to provide insights into improving all the stages of the education process: from forming a curriculum to deciding in which order to present the material to grading the assignments and exams. The authors do not claim to have solved all the problems of education. Instead they show, using numerous examples, that an innovative combination of different uncertainty techniques can improve teaching. The book offers teachers and instructors valuable advice and provides researchers in pedagogical and fuzzy areas with techniques to further advance teaching.

Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems

Автор: Hongyi Li; Ligang Wu; Hak-Keung Lam; Yabin Gao
Название: Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems
ISBN: 9811005923 ISBN-13(EAN): 9789811005923
Издательство: Springer
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Цена: 18284.00 р.
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Описание: This book develops a set of reference methods capable of modeling uncertainties existing in membership functions, and analyzing and synthesizing the interval type-2 fuzzy systems with desired performances.

Fuzzy Preference Ordering of Interval Numbers in Decision Problems

Автор: Atanu Sengupta; Tapan Kumar Pal
Название: Fuzzy Preference Ordering of Interval Numbers in Decision Problems
ISBN: 3642100600 ISBN-13(EAN): 9783642100604
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This text studies different real decision situations where problems are defined in inexact environment. It presents the latest research in fuzzy preference ordering of interval numbers and modeling of interval decision problems.

Beyond Two: Theory and Applications of Multiple-Valued Logic

Автор: Melvin Fitting; Ewa Orlowska
Название: Beyond Two: Theory and Applications of Multiple-Valued Logic
ISBN: 3790825220 ISBN-13(EAN): 9783790825220
Издательство: Springer
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Цена: 23058.00 р.
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Описание: This volume represents the state of the art for much current research in many-valued logics. Areas covered include: Algebras of multiple valued logics and their applications, proof theory and automated deduction in multiple valued logics, fuzzy logics and their applications, and multiple valued logics for control theory and rational belief.

Uncertainty Data in Interval-Valued Fuzzy Set Theory

Автор: P?kala
Название: Uncertainty Data in Interval-Valued Fuzzy Set Theory
ISBN: 3319939092 ISBN-13(EAN): 9783319939094
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov`s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information.

Interval-Valued Methods in Classifications and Decisions

Автор: Urszula Bentkowska
Название: Interval-Valued Methods in Classifications and Decisions
ISBN: 3030129268 ISBN-13(EAN): 9783030129262
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book describes novel algorithms based on interval-valued fuzzy methods that are expected to improve classification and decision-making processes under incomplete or imprecise information. At first, it introduces interval-valued fuzzy sets. It then discusses new methods for aggregation on interval-valued settings, and the most common properties of interval-valued aggregation operators. It then presents applications such as decision making using interval-valued aggregation, and classification in case of missing values. Interesting applications of the developed algorithms to DNA microarray analysis and in medical decision support systems are shown. The book is intended not only as a timely report for the community working on fuzzy sets and their extensions but also for researchers and practitioners dealing with the problems of uncertain or imperfect information.


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