Optimization for industrial problems:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Berlin [u.a.]
Springer
2012
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis Inhaltstext Inhaltsverzeichnis |
| Item Description: | Literaturverz. S. 237 - 241 |
| Physical Description: | XXII, 246 S. teilw. farb. Ill., graph. Darst. 24 cm |
| ISBN: | 9783642249730 3642249736 |
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MARC
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| adam_text |
IMAGE 1
CONTENTS
1 OVERVIEW OF HEURISTIC OPTIMIZATION 1
1.1 WHAT IS OPTIMIZATION? 1
1.1.1 SEARCHING VS. OPTIMIZATION 2
1.1.2 CONSTRAINTS 3
1.1.3 FINDING THROUGH A LITTLE SEARCHING 3
1.1.4 ACCURACY 4
1.1.5 CERTAINTY 4
1.2 EXACT VS. HEURISTIC METHODS 5
1.2.1 EXACT METHODS 5
1.2.2 HEURISTIC METHODS 6
1.2.3 MULTI-OBJECTIVE OPTIMIZATION 7
1.3 PRACTICAL ISSUES 9
1.4 EXAMPLE THEORETICAL PROBLEMS 11
2 STATISTICAL ANALYSIS IN SOLUTION SPACE 13
2.1 BASIC VOCABULARY OF STATISTICAL MECHANICS 14
2.2 POSTULATES OF THE THEORY 18
2.3 ENTROPY 20
2.4 TEMPERATURE 23
2.5 ERGODICITY 25
3 PROJECT MANAGEMENT 29
3.1 WATERFALL MODEL VS. AGILE MODEL 30
3.2 DESIGN OF EXPERIMENTS 34
3.3 PRIORITIZING GOALS 35
4 PRE-PROCESSING: CLEANING UP DATA 37
4.1 DIRTY DATA 37
4.2 DISCRETIZATION 38
4.2.1 TIME-SERIES FROM INSTRUMENTATION 38
4.2.2 DATA NOT ORDERED IN TIME 39
BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/101610555X
DIGITALISIERT DURCH
IMAGE 2
CONTENTS
4.3 OUTLIER DETECTION 40
4.3.1 UNREALISTIC DATA 41
4.3.2 UNLIKELY DATA 41
4.3.3 IRREGULAR AND ABNORMAL DATA 41
4.3.4 MISSING DATA 42
4.4 DATA REDUCTION / FEATURE SELECTION 43
4.4.1 SIMILAR DATA 43
4.4.2 IRRELEVANT DATA 43
4.4.3 REDUNDANT DATA 44
4.4.4 DISTINGUISHING FEATURES 44
4.5 SMOOTHING AND DE-NOISING 47
4.5.1 NOISE 47
4.5.2 SINGULAR SPECTRUM ANALYSIS 48
4.6 REPRESENTATION AND SAMPLING 50
4.7 INTERPOLATION 51
4.8 CASE STUDY: SELF-BENCHMARKING IN MAINTENANCE OF A CHEMICAL PLANT 53
4.8.1 BENCHMARKING 53
4.8.2 SELF-BENCHMARKING 54
4.8.3 RESULTS AND CONCLUSIONS 56
4.9 CASE STUDY: FINANCIAL DATA ANALYSIS FOR CONTRACT PLANNING 58 4.10
CASE STUDY: MEASURING HUMAN INFLUENCE 62
4.11 CASE STUDY: EARLY WARNING SYSTEM FOR IMPORTANCE OF PRODUCTION
ALARMS 63
DATA MINING: KNOWLEDGE FROM DATA 67
5. 1 CONCEPTS OF STATISTICS AND MEASUREMENT 67
5.1.1 POPULATION, SAMPLE AND ESTIMATION 67
5.1.2 MEASUREMENT ERROR AND UNCERTAINTY 68
5.1.3 INFLUENCE OF THE OBSERVER 70
5.1.4 MEANING OF PROBABILITY AND STATISTICS 71
5.2 STATISTICAL TESTING 73
5.2.1 TESTING CONCEPTS 73
5.2.2 SPECIFIC TESTS 75
5.2.2.1 DO TWO DATASETS HAVE THE SAME MEAN? 75
5.2.2.2 DO TWO DATASETS HAVE THE SAME VARIANCE? 76 5.2.2.3 ARE TWO
DATASETS DIFFERENTLY DISTRIBUTED? 76 5.2.2.4 ARE THERE OUTLIERS AND, IF
SO, WHERE? 77
5.2.2.5 HOW WELL DOES THIS MODEL FIT THE DATA? 78
5.3 OTHER STATISTICAL MEASURES 79
5.3.1 REGRESSION 79
5.3.2 ANOVA 81
5.3.3 CORRELATION AND AUTOCORRELATION 84
5.3.4 CLUSTERING 85
5.3.5 ENTROPY 89
5.3.6 FOURIER TRANSFORMATION 91
IMAGE 3
CONTENTS XXI
5.4 CASE STUDY: OPTICAL DIGIT RECOGNITION 92
5.5 CASE STUDY: TURBINE DIAGNOSIS IN A POWER PLANT 96
5.6 CASE STUDY: DETERMINING THE CAUSE OF A KNOWN FAULT 102 5.7 MARKOV
CHAINS AND THE CENTRAL LIMIT THEOREM 105
5.8 BAYESIAN STATISTICAL INFERENCE AND THE NOISY CHANNEL 107 5.8.1
INTRODUCTION TO BAYESIAN INFERENCE 107
5.8.2 DETERMINING THE PRIOR DISTRIBUTION 108
5.8.3 DETERMINING THE SAMPLING DISTRIBUTION 110
5.8.4 NOISY CHANNELS 110
5.8.4.1 BUILDING A NOISY CHANNEL I LL
5.8.4.2 CONTROLLING A NOISY CHANNEL 112
5.9 NON-LINEAR MULTI-DIMENSIONAL REGRESSION 113
5.9.1 LINEAR LEAST SQUARES REGRESSION 113
5.9.2 BASIS FUNCTIONS 114
5.9.3 NONLINEARITY 115
5.10 CASE STUDY: CUSTOMER SEGMENTATION 117
6 MODELING: NEURAL NETWORKS 121
6.1 WHAT IS MODELING? 121
6.1.1 DATA PREPARATION 124
6.1.2 HOW MUCH DATA IS ENOUGH? 125
6.2 NEURAL NETWORKS 126
6.3 BASIC CONCEPTS OF NEURAL NETWORK MODELING 129
6.4 FEED-FORWARD NETWORKS 131
6.5 RECURRENT NETWORKS 132
6.6 CASE STUDY: SCRAP DETECTION IN INJECTION MOLDING MANUFACTURING .
135 6.7 CASE STUDY: PREDICTION OF TURBINE FAILURE 140
6.8 CASE STUDY: FAILURES OF WIND POWER PLANTS 143
6.9 CASE STUDY: CATALYTIC REACTORS IN CHEMISTRY AND PETROCHEMISTRY.
148 6.10 CASE STUDY: PREDICTING VIBRATION CRISES IN NUCLEAR POWER PLANTS
. . 152 6.11 CASE STUDY: IDENTIFYING AND PREDICTING THE FAILURE OF
VALVES 155 6.12 CASE STUDY: PREDICTING THE DYNAMOMETER CARD OF A ROD
PUMP . . . 157
7 OPTIMIZATION: SIMULATED ANNEALING 165
7. 1 GENETIC ALGORITHMS 166
7.2 ELEMENTARY SIMULATED ANNEALING 167
7.3 THEORETICAL RESULTS 169
7.4 COOLING SCHEDULE AND PARAMETERS 172
7.4.1 INITIAL TEMPERATURE 173
7.4.2 STOPPING CRITERION (DEFINITION OF FREEZING) 174 7.4.3 MARKOV CHAIN
LENGTH (DEFINITION OF EQUILIBRIUM) 175 7.4.4 DECREMENT FORMULA FOR
TEMPERATURE (COOLING SPEED) 177 7.4.5 SELECTION CRITERION 178
7.4.6 PARAMETER CHOICE 178
7.5 PERTURBATIONS FOR CONTINUOUS AND COMBINATORIAL PROBLEMS 181
IMAGE 4
XXII CONTENTS
7.6 CASE STUDY: HUMAN BRAINS USE SIMULATED ANNEALING TO THINK 183 7.7
DETERMINING AN OPTIMAL PATH FROM A TO B 186
7.8 CASE STUDY: OPTIMIZATION OF THE MIILLER-ROCHOW SYNTHESIS OF SILANES
189
7.9 CASE STUDY: INCREASE OF OIL PRODUCTION YIELD IN SHALLOW-WATER
OFFSHORE OIL WELLS 194
7.10 CASE STUDY: INCREASE OF COAL BURNING EFFICIENCY IN CHP POWER PLANT
197 7.11 CASE STUDY: REDUCING THE INTERNAL POWER DEMAND OF A POWER PLANT
199
8 THE HUMAN ASPECT IN SUSTAINABLE CHANGE AND INNOVATION 201 8.1
INTRODUCTION 201
8.1.1 DEFINING THE ITEMS: IDEA, INNOVATION, AND CHANGE 202 8.1.2
RESISTANCE TO CHANGE 204
8.2 INTERFACE MANAGEMENT 207
8.2.1 THE DELIBERATE ORGANIZATION 207
8.2.2 THE HEALTHY ORGANIZATION 209
8.3 INNOVATION MANAGEMENT 213
8.4 HANDLING THE HUMAN ASPECT 216
8.4.1 COMMUNICATION 217
8.4.2 KPIS FOR TEAM ENGAGEMENT 219
8.4.3 PROJECT PREPARATION AND SET UP 221
8.4.4 RISK MANAGEMENT 223
8.4.5 ROLES AND RESPONSIBILITIES 226
8.4.6 CAREER DEVELOPMENT AND SUSTAINABLE CHANGE 228 8.4.7 SUSTAINABILITY
IN TRAINING AND LEARNING 231
8.4.8 THE ECONOMIC FACTOR IN SUSTAINABLE INNOVATION 232 8.5 SUMMARY 234
REFERENCES 237
INDEX 243 |
| any_adam_object | 1 |
| author | Bangert, Patrick |
| author_GND | (DE-588)139485627 |
| author_facet | Bangert, Patrick |
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| dewey-full | 519.6 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.6 |
| dewey-search | 519.6 |
| dewey-sort | 3519.6 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| format | Book |
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| illustrated | Illustrated |
| indexdate | 2024-08-21T00:15:04Z |
| institution | BVB |
| isbn | 9783642249730 3642249736 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025334200 |
| oclc_num | 778153322 |
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| owner | DE-29T DE-83 DE-11 DE-188 |
| owner_facet | DE-29T DE-83 DE-11 DE-188 |
| physical | XXII, 246 S. teilw. farb. Ill., graph. Darst. 24 cm |
| publishDate | 2012 |
| publishDateSearch | 2012 |
| publishDateSort | 2012 |
| publisher | Springer |
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| spelling | Bangert, Patrick Verfasser (DE-588)139485627 aut Optimization for industrial problems Patrick Bangert Berlin [u.a.] Springer 2012 XXII, 246 S. teilw. farb. Ill., graph. Darst. 24 cm txt rdacontent n rdamedia nc rdacarrier Literaturverz. S. 237 - 241 Optimierung (DE-588)4043664-0 gnd rswk-swf Optimierung (DE-588)4043664-0 s DE-604 application/pdf http://d-nb.info/101610555X/04 Inhaltsverzeichnis text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3897179&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025334200&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bangert, Patrick Optimization for industrial problems Optimierung (DE-588)4043664-0 gnd |
| subject_GND | (DE-588)4043664-0 |
| title | Optimization for industrial problems |
| title_auth | Optimization for industrial problems |
| title_exact_search | Optimization for industrial problems |
| title_full | Optimization for industrial problems Patrick Bangert |
| title_fullStr | Optimization for industrial problems Patrick Bangert |
| title_full_unstemmed | Optimization for industrial problems Patrick Bangert |
| title_short | Optimization for industrial problems |
| title_sort | optimization for industrial problems |
| topic | Optimierung (DE-588)4043664-0 gnd |
| topic_facet | Optimierung |
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