Описание: In this guide designed for researchers and students of computer science, readers will find a resource for how to apply methods that work on real-life problems to their challenging applications, and a go-to work that makes fuzzy clustering issues and aspects clear.
Автор: Jaime Gil-Aluja Название: Fuzzy Sets in the Management of Uncertainty ISBN: 3642057942 ISBN-13(EAN): 9783642057946 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Fuzzy Sets in the Management of Uncertainty presents an overview of current problems in business management, primarily for those situations involving decision making of an economic-financial nature.
Автор: Asli Celikyilmaz; I. Burhan T?rksen Название: Modeling Uncertainty with Fuzzy Logic ISBN: 3642100635 ISBN-13(EAN): 9783642100635 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". It also reviews standard tools of fuzzy system modeling approaches to demonstrate the novelty of the structurally different fuzzy function.
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 Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Описание: This book provides a number of formulae for implementing the operation extended on fuzzy-valued fuzzy sets, presents basic structures of generalized uncertain fuzzy logic systems, and introduces several of methods to generate fuzzy membership uncertainty.
Описание: Lastly the constraints, expressed by equalities or inequalities between linear expressions, are often softer in reality that what their mathematical expression might let us believe, and infeasibility as detected by the linear programming techniques can often been coped with by making trade-offs with the real world.
Описание: This text examines the use of analytical tools developed for studying uncertainty analysis in engineering, control systems, and the sciences. It is the work of 38 contributors who have each written chapters on developed analytical methods and have applied them to uncertainty phenomena.
Описание: But we know precious little about human reasoning processes, learning mechanisms and the like, and in particular about reasoning with limited, imprecise knowledge. In a sense, intelligent systems are machines which use the most general form of human knowledge together with human reasoning capability to reach decisions.
Описание: Lastly the constraints, expressed by equalities or inequalities between linear expressions, are often softer in reality that what their mathematical expression might let us believe, and infeasibility as detected by the linear programming techniques can often been coped with by making trade-offs with the real world.
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.
Автор: Barbara P?kala Название: Uncertainty Data in Interval-Valued Fuzzy Set Theory ISBN: 3030067432 ISBN-13(EAN): 9783030067434 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: 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. 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.
Описание: The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become.
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