模糊集合论及其应用（第4版） [Fuzzy Set Theory and Its Applications Fourth Edition] 下载 mobi epub pdf 电子书 2024

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内容简介

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.

内页插图

目录

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

精彩书摘

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

模糊集合论及其应用（第4版） [Fuzzy Set Theory and Its Applications Fourth Edition] 下载 mobi epub pdf txt 电子书 格式

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所谓模糊概念是指这个概念的外延具有不确定性，或者说它的外延是不清晰的，是模糊的。例如“青年”这个概念，它的内涵我们是清楚的，但是它的外延，即什么样的年龄阶段内的人是青年，恐怕就很难说情楚，因为在“年轻”和“不年轻”之间没有一个确定的边界，这就是一个模糊概念。

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第四版了，经典必须收藏。

评分☆☆☆☆☆

所谓模糊概念是指这个概念的外延具有不确定性，或者说它的外延是不清晰的，是模糊的。例如“青年”这个概念，它的内涵我们是清楚的，但是它的外延，即什么样的年龄阶段内的人是青年，恐怕就很难说情楚，因为在“年轻”和“不年轻”之间没有一个确定的边界，这就是一个模糊概念。

评分☆☆☆☆☆

包装挺好，书不错。

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东西不错，希望一直好用。

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最后，人们对模糊性的认识往往同随机性混淆起来，其实它们之间有着根本的区别。随机性是其本身具有明确的含义，只是由于发生的条件不充分，而使得在条件与事件之间不能出现确定的因果关系，从而事件的出现与否表现出一种不确定性。而事物的模糊性是指我们要处理的事物的概念本身就是模糊的，即一个对象是否符合这个概念难以确定，也就是由于概念外延模糊而带来的不确定性。

评分☆☆☆☆☆

包装挺好，书不错。

评分☆☆☆☆☆

最后，人们对模糊性的认识往往同随机性混淆起来，其实它们之间有着根本的区别。随机性是其本身具有明确的含义，只是由于发生的条件不充分，而使得在条件与事件之间不能出现确定的因果关系，从而事件的出现与否表现出一种不确定性。而事物的模糊性是指我们要处理的事物的概念本身就是模糊的，即一个对象是否符合这个概念难以确定，也就是由于概念外延模糊而带来的不确定性。

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