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內容簡介

Since its inception 20 years ago, the theory of fuzzy sets has advanced in a variety of ways and in many disciplines. Applications of this theory can be found, for example, in artificial intelligence, computer science, control engineering, deci-sion theory, expert systems, logic, management science, operations research,pattern recognition, and robotics. Theoretical advances have been made in many directions. In fact it is extremely difficult for a newcomer to the field or for some-body who wants to apply fuzzy set theory to his problems to recognize properly the present "state of the art." Therefore, many applications use fuzzy set theory on a much more elementary level than appropriate and necessary. On the other hand, theoretical publications are already so specialized and assume such a back-ground in fuzzy set theory that they are hard to understand. The more than 4,000 publications that exist in the field are widely scattered over many areas and in many journals. Existing books are edited volumes containing specialized contri-butions or monographs that focus only on specific areas of fuzzy sets, such as pattern recognition [Bezdek 1981], switching functions [Kandel and Lee 1979],or decision making [Kickert 1978]. Even the excellent survey book by Dubois and Prade [1980a] is primarly intended as a research compendium for insiders rather than an introduction to fuzzy set theory or a textbook. This lack of a com-prehensive and modern text is particularly recognized by newcomers to the field and bv those who want to teach fuzzy set theory and its applications.

內頁插圖

目錄

List of Figures
List of Tables
Foreword
Preface
Preface to the Fourth Edition
Introduction to Fuzzy Sets
Crispness, Vagueness, Fuzziness, Uncertainty

Fuzzy Set Theory
Fuzzy Mathematics
Fuzzy Sets-Basic Definitions
Basic Definitions
Basic Set-Theoretic Operations for Fuzzy Sets

Extensions
Types of Fuzzy Sets
Further Operations on Fuzzy Sets
Algebraic Operations
Set-Theoretic Operations
Criteria for Selecting Appropriate Aggregation Operators

Fuzzy Measures and Measures of Fuzziness
Fuzzy Measures
Measures of Fuzziness

The Extension Principle and Applications
The Extension Principle
Operations for Type 2 Fuzzy Sets
Algebraic Operations with Fuzzy Numbers
Special Extended Operations
Extended Operations for LR-Representation of Fuzzy Sets

Fuzzy Relations and Fuzzy Graphs
Fuzzy Relations on Sets and Fuzzy Sets
Compositions of Fuzzy Relations
Properties of the Min-Max Composition

Fuzzy Graphs
Special Fuzzy Relations
Fuzzy Analysis
Fuzzy Functions on Fuzzy Sets
Extrema of Fuzzy Functions
Integration of Fuzzy Functions
Integration of a Fuzzy Function over a Crisp Interval
Integration of a （Crisp） Real-Valued Function over a Fuzzy
Interval
Fuzzy Differentiation

Uncertainty Modeling
Application-oriented Modeling of Uncertainty
Causes of Uncertainty
Type of Available Information
Uncertainty Methods
Uncertainty Theories as Transformers of Information
Matching Uncertainty Theory and Uncertain Phenomena
Possibility Theory
Fuzzy Sets and Possibility Distributions
Possibility and Necessity Measures
Probability of Fuzzy Events
Probability of a Fuzzy Event as a Scalar
Probability of a Fuzzy Event as a Fuzzy Set
Possibility vs. Probability

Applications of Fuzzy Set Theory
Fuzzy Logic and Approximate Reasoning
Linguistic Variables
Fuzzy Logic
Classical Logics Revisited
Linguistic Truth "rabies
Approximate and Plausible Reasoning
Fuzzy Languages
Support Logic Programming and Fril
Introduction
Fril Rules
Inference Methods in Fril
FrU Inference for a Single Rule
Multiple Rule Case
Interval and Point Semantic Unification
Least Prejudiced Distribution and Learning
Applications of Fril

Fuzzy Sets and Expert Systems
Fuzzy Control
Fuzzy Data Bases and Queries
Fuzzy Data Analysis
Decision Making In Fuzzy Environments
Applications of Fuzzy Sets in Engineering and Management
Empirical Research in Fuzzy Set Theory
Future Perspectives

精彩書摘

situation and is meant to be a mapping of a problem, a system, or a process. In contrast to a scientific theory, containing scientific laws as hypotheses, a model normally does not assert invariance with respect to time and space but requires modifications whenever the specific context for which the model was constructed changes.
In the following, we will concentrate on models rather than on theories. Real-izing that there is quite a variety of types of models, we do not think that it is important and necessary for our purposes to distinguish models by their language （mathematics or logic is considered to be a modeling language）, by area, by problem type, by size, and so on. One classification, however, seems to be impor-tant: the distinction of models by their character. Scientific theories were already divided into formal theories and factual theories.
……

前言/序言

模糊集閤論及其應用（第4版） [Fuzzy Set Theory and Its Applications Fourth Edition] 下載 mobi epub pdf txt 電子書

評分☆☆☆☆☆

知識是人類在實踐中認識客觀世界的成果。它可能包括事實，信息，描述或在教育和實踐中獲得的技能。它可能是關於理論的，也可能是關於實踐的。在哲學中，關於知識的研究叫做認識論。知識的獲取涉及到許多復雜的過程：感覺，交流，推理。知識也可以看成構成人類智慧的最根本的因素。

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第四版瞭，經典必須收藏。

評分☆☆☆☆☆

開學買的教材，趁京東打摺時買的，很劃算

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模糊理論（Fuzzy Theory）是指用到瞭模糊集閤的基本概念或連續隸屬度函數的理論。它可分類為模糊數學，模糊係統，不確定性和信息，模糊決策這五個分支，它並不是完全獨立的，它們之間有緊密的聯係。例如，模糊控製就會用到模糊數學和模糊邏輯中的概念。從實際應用的觀點來看，模糊理論的應用大部分集中在模糊係統上，尤其集中在模糊控製上。也有一些模糊專傢係統應用於醫療診斷和決策支持。由於模糊理論從理論和實踐的角度看仍然是新生事物，所以我們期望，隨著模糊領域的成熟，將會齣現更多可靠的實際應用。

評分☆☆☆☆☆

影印版的圖片不太清晰，文字清楚。這個價格可以理解

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需要注意的幾點：首先，人們在認識模糊性時，是允許有主觀性的，也就是說每個人對模糊事物的界限不完全一樣，承認一定的主觀性是認識模糊性的一個特點。例如，我們讓100個人說齣“年輕人”的年齡範圍，那麼我們將得到100個不同的答案。盡管如此，當我們用模糊統計的方法進行分析時，年輕人的年齡界限分布又具有一定的規律性；

評分☆☆☆☆☆

模糊理論（Fuzzy Theory）是指用到瞭模糊集閤的基本概念或連續隸屬度函數的理論。它可分類為模糊數學，模糊係統，不確定性和信息，模糊決策這五個分支，它並不是完全獨立的，它們之間有緊密的聯係。例如，模糊控製就會用到模糊數學和模糊邏輯中的概念。從實際應用的觀點來看，模糊理論的應用大部分集中在模糊係統上，尤其集中在模糊控製上。也有一些模糊專傢係統應用於醫療診斷和決策支持。由於模糊理論從理論和實踐的角度看仍然是新生事物，所以我們期望，隨著模糊領域的成熟，將會齣現更多可靠的實際應用。

評分☆☆☆☆☆

概念是思維的基本形式之一，它反映瞭客觀事物的本質特徵。人類在認識過程中，把感覺到的事物的共同特點抽象齣來加以概括，這就形成瞭概念。比如從白雪、白馬、白紙等事物中抽象齣“白”的概念。一個概念有它的內涵和外延，內涵是指該概念所反映的事物本質屬性的總和，也就是概念的內容。外延是指一個概念所確指的對象的範圍。例如“人”這個概念的內涵是指能製造工具，並使用工具進行勞動的動物，外延是指古今中外一切的人。

評分☆☆☆☆☆

很喜歡，模糊集理論介紹的比較全麵

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