Perceptual computing: aiding people in making subjective judgments
Gespeichert in:
Hauptverfasser: | , |
---|---|
Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Hoboken, N.J
Wiley
2010
|
Schriftenreihe: | IEEE Press Series on Computational Intelligence
|
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | XVI, 320 S. graph. Darst. |
ISBN: | 9780470478769 |
Internformat
MARC
LEADER | 00000nam a2200000 c 4500 | ||
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020 | |a 9780470478769 |c cloth |9 978-0-470-47876-9 | ||
035 | |a (OCoLC)699599752 | ||
035 | |a (DE-599)GBV611128578 | ||
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100 | 1 | |a Mendel, Jerry M. |d 1938- |e Verfasser |0 (DE-588)134275918 |4 aut | |
245 | 1 | 0 | |a Perceptual computing |b aiding people in making subjective judgments |c Jerry M. Mendel ; Dongrui Wu |
264 | 1 | |a Hoboken, N.J |b Wiley |c 2010 | |
300 | |a XVI, 320 S. |b graph. Darst. | ||
336 | |b txt |2 rdacontent | ||
337 | |b n |2 rdamedia | ||
338 | |b nc |2 rdacarrier | ||
490 | 0 | |a IEEE Press Series on Computational Intelligence | |
650 | 0 | |a Human-computer interaction | |
650 | 0 | |a Computational intelligence | |
650 | 0 | |a Decision making | |
650 | 0 | |a Fuzzy sets | |
650 | 0 | 7 | |a Entscheidungsfindung |0 (DE-588)4113446-1 |2 gnd |9 rswk-swf |
650 | 0 | 7 | |a Fuzzy-Logik |0 (DE-588)4341284-1 |2 gnd |9 rswk-swf |
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999 | |a oai:aleph.bib-bvb.de:BVB01-020445843 |
Datensatz im Suchindex
_version_ | 1804143097742884864 |
---|---|
adam_text | Contents
Preface
xiii
1
Introduction
1
1.1
Perceptual
Computing
1
1.2
Examples
З
1.2.1
Investment Decision Making
3
1.2.2
Social Judgment Making
5
1.2.3
Hierarchical Decision Making
7
1.2.4
Hierarchical and Distributed Decision Making
9
1.3
Historical Origins of Perceptual Computing
11
1.4
How to Validate the Perceptual Computer
15
1.5
The Choice of Fuzzy Set Models for the Per-C
16
1.6
Keeping the
Per
-С
as Simple as Possible
19
1.7
Coverage of the Book
20
1.8
High-Level Synopses of Technical Details
24
1.8.1
Chapter
2:
Interval Type-2 Fuzzy Sets
24
1.8.2
Chapter
3:
Encoding: From a Word to a Model
—
The
26
Codebook
1.8.3
Chapter
4:
Decoding: From FOUs to a Recommendation
27
1.8.4
Chapter
5:
Novel Weighted Averages as a CWW Engine
29
1.8.5
Chapter
6:
If-Then Rules as a CWW Engine
29
References
31
2
Interval Type-2 Fuzzy Sets
35
2.1
A Brief Review of Type-
1
Fuzzy Sets
35
2.2
Introduction to Interval Type-2 Fuzzy Sets
38
2.3
Definitions
42
2.4
Wavy-Slice Representation Theorem
45
2.5
Set-Theoretic Operations
45
2.6
CentroidofanIT2FS
46
2.6.1
General Results
46
2.6.2
Properties of the Centroid
50
2.7
KM Algorithms
52
vii
VIH
CONTENTS
2.7.1
Derivation of KM Algorithms
52
2.7.2
Statements of KM Algorithms
53
2.7.3
Properties of KM Algorithms
54
2.8
Cardinality and Average Cardinality of an IT2 FS
56
2.9
Final Remark
58
Appendix 2A. Derivation of the Union of Two 1T2 FSs
58
Appendix 2B. Enhanced KM (EKM) Algorithms
59
References
61
3
Encoding: From a Word to a Model
—
The
Codebook 65
65
67
77
77
81
82
83
84
89
99
101
104
105
3.6
Hedges
105
Appendix
ЗА.
Methods for Eliciting Tl
MF
Information From Subjects
107
ЗАЛ
Introduction
107
3A.2 Description of the Methods
107
3A.3 Discussion
110
Appendix 3B. Derivation of Reasonable Interval Test
111
References
114
4
Decoding: From FOUs to a Recommendation
117
4.1
Introduction
117
4.2
Similarity Measure Used as a Decoder
118
4.2.1
Definitions
118
4.2.2
Desirable Properties for an IT2 FS Similarity Measure
119
Used as a Decoder
4.2.3
Problems with Existing IT2 FS Similarity Measures
120
4.2.4
Jaccard Similarity Measure for IT2 FSs
121
4.2.5
Simulation Results
122
4.3
Ranking Method Used as a Decoder
123
4.3.1
Reasonable Ordering Properties for IT2 FSs
128
4.3.2
Mitchell s Method for Ranking IT2 FSs
128
4.3.3
A New Centroid-Based Ranking Method
129
3.1
Introduction
3.2
Person
FOU
Approach for a Group of Subjects
3.3
Collecting Interval End-Point Data
3.3.1
Methodology
3.3.2
Establishing End-Point Statistics For the Data
3.4
Interval
1
End-Points Approach
3.5
Interval
1
Approach
3.5.1
Data Part
3.5.2
Fuzzy Set Part
3.5.3
Observations
3.5.4
Codebook
Example
3.5.5
Software
3.5.6
Concluding Remarks
CONTENTS
ІХ
4.3.4 Simulation
Results
129
4.4
Classifier Used as a Decoder
130
4.4.1
Desirable Properties for Subsethood Measure as a Decoder
130
4.4.2
Problems with Four Existing 1T2 FS Subsethood Measures
131
4.4.3
Vlachos and Sergiadis s IT2 FS Subsethood Measure
131
4.4.4
Simulation Results
132
Appendix
4
A
135
4A.1 Compatibility Measures for
Τ
1
FSs
135
4A.2 Ranking Methods for Tl FSs
137
Appendix 4B
137
4B.1 Proof of Theorem
4.1 137
4B.2 Proof of Theorem
4.2 139
4B.3 Proof of Theorem
4.3 140
References
141
5
Novel Weighted Averages as a CWW Engine
145
5.1
Introduction
145
5.2
Novel Weighted Averages
146
5.3
Interval Weighted Average
147
5.4
Fuzzy Weighted Average
149
5.4.1
α
-cuts and a Decomposition Theorem
149
5.4.2
Functions of
Τ
1
FSs
151
5.4.3
Computing the FWA
152
5.5
Linguistic Weighted Average
154
5.5.1
Introduction
154
5.5.2
Computing the
LWA
157
5.5.3
Algorithms
160
5.6
A Special Case of the
LWA
163
5.7
Fuzzy Extensions of Ordered Weighted Averages
165
5.7.1
Ordered Fuzzy Weighted Averages (OF
WAs)
166
5.7.2
Ordered Linguistic Weighted Averages (OLWAs)
166
Appendix
5
A
167
5
A.
1
Extension Principle
167
5A.2 Decomposition of a Function of
Τ
1
FSs Using
α
-cuts
169
5A.3 Proof of Theorem
5.2 171
References
173
6
IF-THEN Rules as a CWW Engine
—
Perceptual Reasoning
175
6.1
Introduction
175
6.2
A Brief Overview of Interval Type-2 Fuzzy Logic Systems
177
6.2.1
Firing Interval
177
6.2.2
Fired-Rule Output
FOU
178
6.2.3
Aggregation of Fired-Rule Output FOUs
178
6.2.4
Type-Reduction and Defuzzification
178
CONTENTS
6.2.5
Observations
179
6.2.6
A Different Way to Aggregate Fired Rules by Blending
180
Attributes
6.3
Perceptual Reasoning: Computations
180
6.3.1
Computing Firing Levels
181
6.3.2
Computing YPR
182
6.4
Perceptual Reasoning: Properties
184
6.4.1
General Properties About the Shape of YPR
185
6.4.2
Properties of YPR FOUs
186
6.5
Examples
187
Appendix 6A
191
6A.1
Proof of Theorem
6.1
191
6A.2
Proof of Theorem
6.2
191
6A.3
Proof of Theorem
6.3
191
6A.4
Proof of Theorem
6.4
192
6A.5
Proof of Theorem
6.5
192
6A.6
Proof of Theorem
6.6
192
6A.7
Proof of Theorem
6.7
193
6A.8
Proof of Theorem
6.8
194
References
195
7
Assisting in Making Investment Choices
—
Investment Judgment
199
Advisor (IJA)
7.1
Introduction
199
7.2
Encoder for the IJA
202
7.2.1
Vocabulary
202
7.2.2
Word FOUs and
Codebooks
203
7.3
Reduction of the
Codebooks
to User-Friendly
Codebooks
204
7.4
CWW Engine for the IJA
214
7.5
Decoder for the IJA
215
7.6
Examples
216
7.6.1
Example
1:
Comparisons for Three Kinds of Investors
216
7.6.2
Example
2:
Sensitivity of IJA to the Linguistic Ratings
221
7.7
Interactive Software for the IJA
228
7.8
Conclusions
228
References
233
8
Assisting in Making Social Judgments
—
Social Judgment Advisor
235
(SJA)
8.1
Introduction
235
8.2
Design an
SJA
235
8.2.1
Methodology
236
8.2.2
Some Survey Results
238
8.2.3
Data
Pre-
Processing
238
CONTENTS
XI
8.2.4 Rulebase Generation 242
8.2.5 Computing
the
Output
of the
SJA
245
8.3
Using an
SJA
246
8.3.1 Single
Antecedent Rules: Touching and Flirtation
247
8.3.2
Single Antecedent Rules: Eye Contact and Flirtation
249
8.3.3
Two-Antecedent Rules: Touching/Eye Contact and
251
Flirtation
8.3.4
On Multiple Indicators
253
8.3.5
On First and Succeeding Encounters
255
8.4
Discussion
255
8.5
Conclusions
256
References
257
9
Assisting in Hierarchical Decision Making
—
Procurement Judgment
259
Advisor (PJA)
9.1
Introduction
259
9.2
Missile Evaluation Problem Statement
260
9.3
Per
-С
for Missile Evaluation: Design
, 263
9.3.1
Encoder
263
9.3.2
CWW Engine
265
9.3.3
Decoder
266
9.4
Per
-С
for Missile Evaluation: Examples
266
9.5
Comparison with Previous Approaches
273
9.5.1
Comparison with
Mon et al. s
Approach
273
9.5.2
Comparison with Chen s First Approach
276
9.5.3
Comparison with Chen s Second Approach
278
9.5.4
Discussion
279
9.6
Conclusions
280
Appendix 9A: Some Hierarchical Multicriteria Decision-Making
280
Applications
References
282
10
Assisting in Hierarchical and Distributed Decision Making
— 283
Journal Publication Judgment Advisor (JPJA)
10.1
Introduction
283
10.2
The Journal Publication Judgment Advisor (JPJA)
284
10.3
Per
-С
for the JPJA
285
10.3.1
Modified Paper Review Form
285
10.3.2
Encoder
286
10.3.3
CWW Engine
288
10.3.4
Decoder
290
10.4
Examples
291
10.4.1
Aggregation of Technical Merit Subcriteria
291
10.4.2
Aggregation of Presentation Subcriteria
294
XU CONTENTS
10.4.3 Aggregation
at the Reviewer
Level 299
10.4.4
Aggregation at the AE Level
300
10.4.5
Complete Reviews
304
10.5
Conclusions
309
Reference
310
11
Conclusions
311
11.1
Perceptual Computing Methodology
311
11.2
Proposed Guidelines for Calling Something CWW
312
Index
315
|
any_adam_object | 1 |
author | Mendel, Jerry M. 1938- Wu, Dongrui |
author_GND | (DE-588)134275918 |
author_facet | Mendel, Jerry M. 1938- Wu, Dongrui |
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building | Verbundindex |
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ctrlnum | (OCoLC)699599752 (DE-599)GBV611128578 |
dewey-full | 006.3 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 006 - Special computer methods |
dewey-raw | 006.3 |
dewey-search | 006.3 |
dewey-sort | 16.3 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
format | Book |
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id | DE-604.BV036523887 |
illustrated | Illustrated |
indexdate | 2024-07-09T22:42:15Z |
institution | BVB |
isbn | 9780470478769 |
language | English |
lccn | 2009041401 |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-020445843 |
oclc_num | 699599752 |
open_access_boolean | |
owner | DE-91 DE-BY-TUM DE-473 DE-BY-UBG |
owner_facet | DE-91 DE-BY-TUM DE-473 DE-BY-UBG |
physical | XVI, 320 S. graph. Darst. |
publishDate | 2010 |
publishDateSearch | 2010 |
publishDateSort | 2010 |
publisher | Wiley |
record_format | marc |
series2 | IEEE Press Series on Computational Intelligence |
spelling | Mendel, Jerry M. 1938- Verfasser (DE-588)134275918 aut Perceptual computing aiding people in making subjective judgments Jerry M. Mendel ; Dongrui Wu Hoboken, N.J Wiley 2010 XVI, 320 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier IEEE Press Series on Computational Intelligence Human-computer interaction Computational intelligence Decision making Fuzzy sets Entscheidungsfindung (DE-588)4113446-1 gnd rswk-swf Fuzzy-Logik (DE-588)4341284-1 gnd rswk-swf Fuzzy-Logik (DE-588)4341284-1 s Entscheidungsfindung (DE-588)4113446-1 s DE-604 Wu, Dongrui Verfasser aut Digitalisierung UB Bamberg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020445843&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Mendel, Jerry M. 1938- Wu, Dongrui Perceptual computing aiding people in making subjective judgments Human-computer interaction Computational intelligence Decision making Fuzzy sets Entscheidungsfindung (DE-588)4113446-1 gnd Fuzzy-Logik (DE-588)4341284-1 gnd |
subject_GND | (DE-588)4113446-1 (DE-588)4341284-1 |
title | Perceptual computing aiding people in making subjective judgments |
title_auth | Perceptual computing aiding people in making subjective judgments |
title_exact_search | Perceptual computing aiding people in making subjective judgments |
title_full | Perceptual computing aiding people in making subjective judgments Jerry M. Mendel ; Dongrui Wu |
title_fullStr | Perceptual computing aiding people in making subjective judgments Jerry M. Mendel ; Dongrui Wu |
title_full_unstemmed | Perceptual computing aiding people in making subjective judgments Jerry M. Mendel ; Dongrui Wu |
title_short | Perceptual computing |
title_sort | perceptual computing aiding people in making subjective judgments |
title_sub | aiding people in making subjective judgments |
topic | Human-computer interaction Computational intelligence Decision making Fuzzy sets Entscheidungsfindung (DE-588)4113446-1 gnd Fuzzy-Logik (DE-588)4341284-1 gnd |
topic_facet | Human-computer interaction Computational intelligence Decision making Fuzzy sets Entscheidungsfindung Fuzzy-Logik |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020445843&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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