Fuzzy Decision Procedures with Binary Relations, Leonid Kitainik

Автор: Zaiwu Gong; Yi Lin; Tianxiang Yao
Название: Uncertain Fuzzy Preference Relations and Their Applications
ISBN: 3642427901 ISBN-13(EAN): 9783642427909
Издательство: Springer
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Цена: 16977.00 р.
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Описание: This book explores group decision-making in various scenarios of preference relations, studying the consistency of group decision making using mathematical reasoning, probing decision alternatives using soft computing and optimization and more.

Автор: Young-Jou Lai; Ching-Lai Hwang
Название: Fuzzy Multiple Objective Decision Making
ISBN: 3540575952 ISBN-13(EAN): 9783540575955
Издательство: Springer
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Цена: 20263.00 р.
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Описание: Methods of crisp, fuzzy and possibilistic multiple objective decision-making are systematically reviewed and classified in this volume. The reader is provided with a survey of existing methods and their application to the analysis of fuzzy programming problems.

Автор: F.P. Hwang; Shu-Jen Chen; Ching-Lai Hwang
Название: Fuzzy Multiple Attribute Decision Making
ISBN: 3540549986 ISBN-13(EAN): 9783540549987
Издательство: Springer
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Цена: 18167.00 р.
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Описание: In this monograph, the literature on methods of fuzzy Multiple Attribute Decision Making (MADM) has been reviewed thoroughly and critically, and classified systematically. The basic concepts and algorithms from the classical MADM methods have been used in the development of the fuzzy MADM methods.

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.

Автор: Leonid Kitainik
Название: Fuzzy Decision Procedures with Binary Relations
ISBN: 9401048665 ISBN-13(EAN): 9789401048668
Издательство: Springer
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Цена: 20962.00 р.
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Описание: In decision theory there are basically two appr~hes to the modeling of individual choice: one is based on an absolute representation of preferences leading to a ntDnerical expression of preference intensity.

Автор: O. Kubaschewski; O. Kubaschewski
Название: IRON—Binary Phase Diagrams
ISBN: 3662080265 ISBN-13(EAN): 9783662080269
Издательство: Springer
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Цена: 13060.00 р.
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Описание: When I congratulated him on the well deserved success of his "Aufbau der Zweistoff-Legierungen", he smiled: "yes, it was a struggle with the hydra, and so it has taken me seven years", meaning that whenever he had thought to have finished the phase diagram of a particular system, new evidence would turn up like the new heads of the Greek monster.

Автор: Koutarou Kyutoku
Название: The Black Hole-Neutron Star Binary Merger in Full General Relativity
ISBN: 4431547339 ISBN-13(EAN): 9784431547334
Издательство: Springer
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Цена: 13059.00 р.
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Описание: This title examines orbital evolution, gravitational wave radiation and merger remnant of the black hole-neutron star binary merger in full general relativity. It clarifies formation of massive accretion disks for short-hard gamma-ray bursts.

Автор: Yuji Yoshida
Название: Dynamical Aspects in Fuzzy Decision Making
ISBN: 3790824909 ISBN-13(EAN): 9783790824902
Издательство: Springer
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Цена: 23757.00 р.
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Описание: Dynamic programming, advo- cated in Bellmans book "Dynamic programming" (1957), is one of the most powerful tools to deal with dynamics in systems, and Bellman and Zadeh has proposed the optimality principle in fuzzy decision making by (1970) introducing fuzzy dynamic programming.

Автор: Kahraman
Название: Fuzzy Statistical Decision-Making
ISBN: 3319390120 ISBN-13(EAN): 9783319390123
Издательство: Springer
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Цена: 20896.00 р.
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Описание: This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas and developments.