Introduction to Fuzzy logic using MATLAB:
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2007
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017443536&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XIV, 430 S. Ill., graph. Darst. 24 cm |
| ISBN: | 3540357807 9783540357803 |
Internformat
MARC
| LEADER | 00000nam a2200000zc 4500 | ||
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| 008 | 070706s2007 xx ad|| |||| 00||| eng d | ||
| 020 | |a 3540357807 |9 3-540-35780-7 | ||
| 020 | |a 9783540357803 |9 978-3-540-35780-3 | ||
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| 035 | |a (DE-599)BVBBV023801337 | ||
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| 084 | |a ST 301 |0 (DE-625)143651: |2 rvk | ||
| 100 | 1 | |a Sivanandam, S. N. |e Verfasser |0 (DE-588)132409747 |4 aut | |
| 245 | 1 | 0 | |a Introduction to Fuzzy logic using MATLAB |c S. N. Sivanandam, S. Sumathi, and S. N. Deepa |
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 2007 | |
| 300 | |a XIV, 430 S. |b Ill., graph. Darst. |c 24 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 630 | 0 | 4 | |a MATLAB |
| 650 | 4 | |a Fuzzy mantığı - Bilgi işlem | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Fuzzy logic |x Data processing | |
| 650 | 0 | 7 | |a MATLAB |0 (DE-588)4329066-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Fuzzy-Logik |0 (DE-588)4341284-1 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Fuzzy-Logik |0 (DE-588)4341284-1 |D s |
| 689 | 0 | 1 | |a MATLAB |0 (DE-588)4329066-8 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Sumathi, Sai |d 1968- |e Verfasser |0 (DE-588)132409720 |4 aut | |
| 700 | 1 | |a Deepa, S. N. |e Verfasser |4 aut | |
| 856 | 4 | 2 | |m Digitalisierung UB Bayreuth |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017443536&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-017443536 | |
Datensatz im Suchindex
| _version_ | 1819291920239689728 |
|---|---|
| adam_text | Contents
1
Introduction
............................................... 1
1.1
Fuzzy Logic
............................................. 1
1.2
Mat LAB
-
An Overview
................................. 6
2
Classical Sets and Fuzzy Sets
.............................. 11
2.1
Introduction
............................................ 11
2.2
Classical Set
............................................ 11
2.2.1
Operations on Classical Sets
........................ 12
2.2.2
Properties of Classical Sets
......................... 14
2.2.3
Mapping of Classical Sets to a Function
.............. 16
2.2.4
Solved Examples
.................................. 17
2.3
Fuzzy Sets
.............................................. 19
2.3.1
Fuzzy Set Operations
.............................. 20
2.3.2
Properties of Fuzzy Sets
............................ 22
2.3.3
Solved Examples
.................................. 23
3
Classical and Fuzzy Relations
.............................. 37
3.1
Introduction
............................................ 37
3.2
Cartesian Product of Relation
............................. 37
3.3
Classical Relations
....................................... 38
3.3.1
Cardinality of Crisp Relation
....................... 39
3.3.2
Operations on Crisp Relation
....................... 39
3.3.3
Properties of Crisp Relations
....................... 40
3.3.4
Composition
...................................... 40
3.4
Fuzzy Relations
......................................... 41
3.4.1
Cardinality of Fuzzy Relations
...................... 41
3.4.2
Operations on Fuzzy Relations
...................... 42
3.4.3
Properties of Fuzzy Relations
....................... 42
3.4.4
Fuzzy Cartesian Product and Composition
........... 43
3.5
Tolerance and Equivalence Relations
....................... 51
3.5.1
Crisp Relation
.................................... 51
XII Contents
3.5.2
Fuzzy Relation
.................................... 53
3.5.3
Solved Examples
.................................. 53
4
Membership Functions
.................................... 73
4.1
Introduction
............................................ 73
4.2
Features of Membership Function
.......................... 73
4.3
Classification of Fuzzy Sets
............................... 75
4.4
Fuzzification
............................................ 76
4.5
Membership Value Assignments
.......................... 76
4.5.1
Intuition
......................................... 77
4.5.2
Inference
......................................... 78
4.5.3
Rank Ordering
................................... 80
4.5.4
Angular Fuzzy Sets
................................ 80
4.5.5
Neural Networks
.................................. 81
4.5.6
Genetic Algorithm
................................. 84
4.5.7
Inductive Reasoning
............................... 84
4.6
Solved Examples
........................................ 85
5
Denazification
............................................. 95
5.1
Introduction
............................................ 95
5.2
Lambda Cuts for Fuzzy Sets
.............................. 95
5.3
Lambda Cuts for Fuzzy Relations
......................... 96
5.4
Denazification Methods
.................................. 96
5.5
Solved Examples
........................................101
6
Fuzzy Rule-Based System
.................................113
6.1
Introduction
............................................113
6.2
Formation of Rules
......................................113
6.3
Decomposition of Rules
..................................115
6.4
Aggregation of Fuzzy Rules
...............................117
6.5
Properties of Set of Rules
.................................117
6.6
Fuzzy Inference System
..................................118
6.6.1
Construction and Working of Inference System
........118
6.6.2
Fuzzy Inference Methods
...........................119
6.6.3
Mamdani s Fuzzy Inference Method
..................120
6.6.4
Takagi-Sugeno Fuzzy Method (TS Method)
..........123
6.6.5
Comparison Between Sugeno and Mamdani Method
. . . 126
6.6.6
Advantages of Sugeno and Mamdani Method
.........127
6.7
Solved Examples
........................................127
7
Fuzzy Decision Making
....................................151
7.1
Introduction
............................................151
7.2
Fuzzy Ordering
.........................................151
7.3
Individual Decision Making
...............................153
7.4
Multi-Person Decision Making
............................153
Contents XIII
7.5
Multi-Objective Decision Making
..........................154
7.6
Fuzzy Bayesian Decision Method
..........................155
Applications of Fuzzy Logic
................................157
8.1
Fuzzy Logic in Power Plants
..............................157
8.1.1
Fuzzy Logic Supervisory Control for Coal Power Plant
. 157
8.2
Fuzzy Logic Applications in Data Mining
...................166
8.2.1
Adaptive Fuzzy Partition in Data Base Mining:
Application to
Olfaction
............................166
8.3
Fuzzy Logic in Image Processing
..........................172
8.3.1
Fuzzy Image Processing
............................172
8.4
Fuzzy Logic in
Biomedicine
...............................200
8.4.1
Fuzzy Logic-Based Anesthetic Depth Control
.........200
8.5
Fuzzy Logic in Industrial and Control Applications
..........204
8.5.1
Fuzzy Logic Enhanced Control of an AC Induction
Motor with a DSP
.................................204
8.5.2
Truck Speed
Limiter
Control by Fuzzy Logic
..........210
8.5.3
Analysis of Environmental Data for Traffic Control
Using Fuzzy Logic
.................................217
8.5.4
Optimization of a Water Treatment System Using
Fuzzy Logic
......................................223
8.5.5
Fuzzy Logic Applications in Industrial Automation
.... 231
8.5.6
Fuzzy Knowledge-Based
Sjetém
for the Control of a
Refuse Incineration Plant Refuse Incineration
.........243
8.5.7
Application of Fuzzy Control for Optimal Operation
of Complex Chilling Systems
........................250
8.5.8
Fuzzy Logic Control of an Industrial Indexing Motion
Application
.......................................255
8.6
Fuzzy Logic in Automotive Applications
....................264
8.6.1
Fuzzy Antilock Brake System
.......................264
8.6.2
Antilock-Braking System and Vehicle Speed
Estimation Using Fuzzy Logic
.......................269
8.7
Application of Fuzzy Expert System
.......................277
8.7.1
Applications of Hybrid Fuzzy Expert Systems in
Computer Networks Design
.........................277
8.7.2
Fuzzy Expert System for Drying Process Control
......288
8.7.3
A Fuzzy Expert System for Product Life Cycle
Management
......................................295
8.7.4
A Fuzzy Expert System Design for Diagnosis of
Prostate Cancer
...................................304
8.7.5
The Validation of a Fuzzy Expert System for Umbilical
Cord Acid-Base Analysis
...........................309
8.7.6
A Fuzzy Expert System Architecture Implementing
Onboard Planning and Scheduling for Autonomous
Small Satellite
....................................313
XIV Contents
8.8
Fuzzy Logic Applications in Power Systems
.................321
8.8.1
Introduction to Power System Control
...............321
8.9
Fuzzy Logic in Control
...................................343
8.9.1
Fuzzy Logic Controller
.............................343
8.9.2
Automatic Generation Control Using Fuzzy Logic
Controllers
.......................................356
8.10
Fuzzy Pattern Recognition
................................359
8.10.1
Multifeature Pattern Recognition
....................367
9
Fuzzy Logic Projects with
Matlab
.........................369
9.1
Fuzzy Logic Control of a Switched Reluctance Motor
.........369
9.1.1
Motor
............................................370
9.1.2
Motor Simulation
.................................370
9.1.3
Current Reference Setting
..........................371
9.1.4
Choice of the Phase to be Fed
......................373
9.2
Modelling and Fuzzy Control of DC Drive
..................375
9.2.1
Linear Model of DC Drive
..........................376
9.2.2
Using PSB to Model the DC Drive
..................378
9.2.3
Fuzzy Controller of DC Drive
.......................378
9.2.4
Results
...........................................380
9.3
Fuzzy Rules for Automated Sensor Self-Validation and
Confidence Measure
.....................................380
9.3.1
Preparation of Membership Functions
................382
9.3.2
Fuzzy Rules
......................................383
9.3.3
Implementation
...................................384
9.4
FLC of Cart
............................................387
9.5
A Simple Fuzzy Excitation Control System (AVR) in Power
System Stability Analysis
.................................392
9.5.1
Transient Stability Analysis
.........................393
9.5.2
Automatic Voltage Regulator
.......................393
9.5.3
Fuzzy Logic Controller Results Applied to a One
Synchronous Machine System
.......................394
9.5.4
Fuzzy Logic Controller in an
18
Bus Bar System
......396
9.6
A Low Cost Speed Control System of Brushless DC Motor
Using Fuzzy Logic
.......................................398
9.6.1
Proposed System
..................................399
9.6.2
Fuzzy Inference System
............................401
9.6.3
Experimental Result
...............................402
Appendix A Fuzzy Logic in
Matlab
.........................409
References
.....................................................419
|
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| author | Sivanandam, S. N. Sumathi, Sai 1968- Deepa, S. N. |
| author_GND | (DE-588)132409747 (DE-588)132409720 |
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| callnumber-search | QA9.64 |
| callnumber-sort | QA 19.64 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | ST 301 |
| ctrlnum | (OCoLC)71336525 (DE-599)BVBBV023801337 |
| dewey-full | 511.3/130285 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 511 - General principles of mathematics |
| dewey-raw | 511.3/130285 |
| dewey-search | 511.3/130285 |
| dewey-sort | 3511.3 6130285 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Mathematik |
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| id | DE-604.BV023801337 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T13:34:25Z |
| institution | BVB |
| isbn | 3540357807 9783540357803 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017443536 |
| oclc_num | 71336525 |
| open_access_boolean | |
| owner | DE-634 DE-29T DE-83 DE-703 |
| owner_facet | DE-634 DE-29T DE-83 DE-703 |
| physical | XIV, 430 S. Ill., graph. Darst. 24 cm |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Springer |
| record_format | marc |
| spellingShingle | Sivanandam, S. N. Sumathi, Sai 1968- Deepa, S. N. Introduction to Fuzzy logic using MATLAB MATLAB Fuzzy mantığı - Bilgi işlem Datenverarbeitung Fuzzy logic Data processing MATLAB (DE-588)4329066-8 gnd Fuzzy-Logik (DE-588)4341284-1 gnd |
| subject_GND | (DE-588)4329066-8 (DE-588)4341284-1 |
| title | Introduction to Fuzzy logic using MATLAB |
| title_auth | Introduction to Fuzzy logic using MATLAB |
| title_exact_search | Introduction to Fuzzy logic using MATLAB |
| title_full | Introduction to Fuzzy logic using MATLAB S. N. Sivanandam, S. Sumathi, and S. N. Deepa |
| title_fullStr | Introduction to Fuzzy logic using MATLAB S. N. Sivanandam, S. Sumathi, and S. N. Deepa |
| title_full_unstemmed | Introduction to Fuzzy logic using MATLAB S. N. Sivanandam, S. Sumathi, and S. N. Deepa |
| title_short | Introduction to Fuzzy logic using MATLAB |
| title_sort | introduction to fuzzy logic using matlab |
| topic | MATLAB Fuzzy mantığı - Bilgi işlem Datenverarbeitung Fuzzy logic Data processing MATLAB (DE-588)4329066-8 gnd Fuzzy-Logik (DE-588)4341284-1 gnd |
| topic_facet | MATLAB Fuzzy mantığı - Bilgi işlem Datenverarbeitung Fuzzy logic Data processing Fuzzy-Logik |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017443536&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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