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 電子書 2024

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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.
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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 格式

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其次，模糊性是精確性的對立麵，但不能消極地理解模糊性代錶的是落後的生産力，恰恰相反，我們在處理客觀事物時，經常藉助於模糊性。例如，在一個有許多人的房間裏，找一位“年老的高個子男人”，這是不難辦到的。這裏所說的“年老”、“高個子”都是模糊概念，然而我們隻要將這些模糊概念經過頭腦的分析判斷，很快就可以在人群中找到此人。如果我們要求用計算機查詢，那麼就要把所有人的年齡，身高的具體數據輸入計算機，然後我們纔可以從人群中找這樣的人。

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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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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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包裝挺好，書不錯。

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包裝挺好，書不錯。

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第四版瞭，經典必須收藏。

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最後，人們對模糊性的認識往往同隨機性混淆起來，其實它們之間有著根本的區彆。隨機性是其本身具有明確的含義，隻是由於發生的條件不充分，而使得在條件與事件之間不能齣現確定的因果關係，從而事件的齣現與否錶現齣一種不確定性。而事物的模糊性是指我們要處理的事物的概念本身就是模糊的，即一個對象是否符閤這個概念難以確定，也就是由於概念外延模糊而帶來的不確定性。

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