模糊集合论及其应用

所属分类:数学  
出版时间:2011-6   出版时间:世界图书出版公司   作者:齐默尔曼   页数:514  
Tag标签:不错,数学  

内容概要

  《模糊集合论及其应用(第4版)》旨在为模糊理论方面的学者提供一部入门级教程,不仅满足了学生学习的需要,也很适合相关的专家学习深入研究。为了使本书不仅仅是一部初级教程,读者范围更加广泛,增加了许多参考资料。知识体系新颖,时代气息十足,不仅是对模糊理论的最现代解释,也很适合学习该理论的应用技巧。虽然是模糊集合理论的初期阶段,该理论得到了广泛的发展,在人工智能,计算机科学,控制工程决策论,专家系统,逻辑学,广利科学,运筹学,机器人技术等众多领域中模糊技术都有广泛的应用,在理论研究方面也取得了突破性进展,作为第四版,有关概率论,模糊逻辑和近似推理,专家系统,模糊控制,模糊数据分析,决策理论和运筹学中模糊模型等章节都做了更新和扩展,并且包括了不少练习。目次:模糊集导论;(第一部分)模糊数学:模糊集合,基本定义;扩展;模糊测度和模糊的测量;扩展原理及应用;模糊关系和模糊图;模糊分析;不确定模型;模糊集合理论应用;模糊集合和专家系统;模糊控制;模糊数据库和疑问;模糊数据分析;模糊环境中决策;工程和管理中模糊集合的应用;模糊集合理论中的经验研究;展望未来。
  读者对象:数学专业研究生,计算机科学,人工智能,工程科学和相关科研人员。

书籍目录

list of figures
list of tables
foreword
preface
preface to the fourth edition
1 introduction to fuzzy sets
1.1 crispness, vagueness, fuzziness, uncertainty
1.2 fuzzy set theory
part i: fuzzy mathematics
2 fuzzy sets--basic definitions
2.1 basic definitions
2.2 basic set-theoretic operations for fuzzy sets
3 extensions
3.1 types of fuzzy sets
3.2 further operations on fuzzy sets
3.2.1 algebraic operations
3.2.2 set-theoretic operations
3.2.3 criteria for selecting appropriate aggregation
operators
4 fuzzy measures and measures of fuzziness
4.1 fuzzy measures
4.2 measures of fuzziness
5 the extension principle and applications
5.1 the extension principle
5.2 operations for type 2 fuzzy sets
5.3 algebraic operations with fuzzy numbers
5.3.1 special extended operations
5.3.2 extended operations for lr-representation of fuzzy sets
6 fuzzy relations and fuzzy graphs
6.1 fuzzy relations on sets and fuzzy sets
6.1.1 compositions of fuzzy relations
6.1.2 properties of the min-max composition
8.2 fuzzy graphs
6.3 special fuzzy relations
7 fuzzy analysis
7.1 fuzzy functions on fuzzy sets
7.2 extrema of fuzzy functions
7.3 integration of fuzzy functions
7.3.1 integration of a fuzzy function over a crisp interval
7.3.2 integration of a (crisp) real-valued function over a fuzzy
interval
7.4 fuzzy differentiation
8 uncertainty modeling
8.1 application-oriented modeling of uncertainty
8.1.1 causes of uncertainty
8.1.2 type of available information
8.1.3 uncertainty methods
8.1.4 uncertainty theories as transformers of information
8.1.5 matching uncertainty theory and uncertain phenomena
8.2 possibility theory
8.2.1 fuzzy sets and possibility distributions
8.2.2 possibility and necessity measures
8.3 probability of fuzzy events
8.3.1 probability of a fuzzy event as a scalar
8.3.2 probability of a fuzzy event as a fuzzy set
8.4 possibility vs. probability
part ii: applications of fuzzy set theory
9 fuzzy logic and approximate reasoning
9.1 linguistic variables
9.2 fuzzy logic
9.2.1 classical logics revisited
9.2.2 linguistic truth tables
9.3 approximate and plausible reasoning
9.4 fuzzy languages
9.5 support logic programming and fril
9.5.1 introduction
9.5.2 fril rules
9.5.3 inference methods in fril
9.5.4 fril inference for a single rule
9.5.5 multiple rule case
9.5.6 interval and point semantic unification
9.5.7 least prejudiced distribution and learning
9.5.8 applications of fril
10 fuzzy sets and expert systems
10.1 introduction to expert systems
10.2 uncertainty modeling in expert systems
10.3 applications
11 fuzzy control
11.1 origin and objective
11.2 automatic control
11.3 the fuzzy controller
11.4 types of fuzzy controllers
11.4.1 the mamdani controller
11.4.2 defuzzification
11.4.3 the sugeno controller
11.5 design parameters
11.5.1 scaling factors
11.5.2 fuzzy sets
11.5.3 rules
11.6 adaptive fuzzy control
11.7 applications
11.7.1 crane control
11.7.2 control of a model car
11.7.3 control of a diesel engine
11.7.4 fuzzy control of a cement kiln
11.8 tools
11.9 stability
11.10 extensions
12 fuzzy data bases and queries
12.1 introduction
12.2 fuzzy relational databases
12.3 fuzzy queries in crisp databases
13 fuzzy data analysis
13.1 introduction
13.2 methods for fuzzy data analysis
13.2.1 algorithmic approaches
13.2.2 knowledge-based approaches
13.2.3 neural net approaches
13.3 dynamic fuzzy data analysis
13.3.1 problem description
13.3.2 similarity of functions
13.3.3 approaches for analysic dynamic systems
13.4 tools for fuzzy data analysis
13.4.1 requirements for fda tools
13.4.2 data engine
13.5 applications of fda
13.5.1 maintenance management in petrochemical plants
13.5.2 acoustic quality control
14 decision making in fuzzy environments
14.1 fuzzy decisions
14.2 fuzzy linear programming
14.2.1 symmetric fuzzy lp
14.2.2 fuzzy lp with crisp objective function
14.3 fuzzy dynamic programming
14.3.1 fuzzy dynamic programming with crisp state transformation
function
14.4 fuzzy multicriteria analysis
14.4.1 multi objective decision making (modm)
14.4.2 multi attributive decision making (madm)
15 applications of fuzzy sets in engineering and management
15.1 introduction
15.2 engineering applications
15.2.1 linguistic evaluation and ranking of machine tools
15.2.2 fault detection in gearboxes
15.3 applications in management
15.3.1 a discrete location model
15.3.2 fuzzy set models in logistics
15.3.2.1 fuzzy approach to the transportation problem
15.3.2.2 fuzzy linear programming in logistics
15.3.3 fuzzy sets in scheduling
15.3.3.1 job-shop scheduling with expert systems
15.3.3.2 a method to control flexible manufacturing systems
15.3.3.3 aggregate production and inventory planning
15.3.3.4 fuzzy mathematical programming for maintenance
scheduling
15.3.3.5 scheduling courses, instructors, and classrooms
15.3.4 fuzzy set models in inventory control
15.3.5 fuzzy sets in marketing
15.3.5.1 customer segmentation in banking and finance
15.3.5.2 bank customer segmentation based on customer
behavior
16 empirical research in fuzzy set theory
16.1 formal theories vs. factual theories vs. decision
technologies
16.1.1 models in operations research and management science
16.1.2 testing factual models
16.2 empirical research on membership functions
16.2.1 type a-membership model
16.2.2 type b-membership model
16.3 empirical research on aggregators
16.4 conclusions
17 future perspectives
abbreviations of frequently cited journals
bibliography
index

章节摘录

  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.  ……

图书封面

图书标签Tags

不错,数学


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用户评论 (总计24条)

 
 

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