Simulation: the practice of model development and use
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Chichester [u.a.]
Wiley
2007
|
| Ausgabe: | Reprint. |
| Schlagworte: | |
| Online-Zugang: | Contributor biographical information Publisher description Table of contents Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XIX, 316 S. Ill., graph. Darst. 24 cm |
| ISBN: | 0470847727 9780470847725 |
Internformat
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| 100 | 1 | |a Robinson, Stewart |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Simulation |b the practice of model development and use |c Stewart Robinson |
| 250 | |a Reprint. | ||
| 264 | 1 | |a Chichester [u.a.] |b Wiley |c 2007 | |
| 300 | |a XIX, 316 S. |b Ill., graph. Darst. |c 24 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
| 650 | 4 | |a aComputer simulation | |
| 650 | 4 | |a aSimulation methods | |
| 650 | 0 | 7 | |a Modellierung |0 (DE-588)4170297-9 |2 gnd |9 rswk-swf |
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| 689 | 0 | 1 | |a Modellierung |0 (DE-588)4170297-9 |D s |
| 689 | 0 | |5 DE-604 | |
| 856 | 4 | |u http://www.loc.gov/catdir/bios/wiley045/2003063093.html |3 Contributor biographical information | |
| 856 | 4 | |u http://www.loc.gov/catdir/description/wiley041/2003063093.html |3 Publisher description | |
| 856 | 4 | |u http://www.loc.gov/catdir/toc/wiley041/2003063093.html |3 Table of contents | |
| 856 | 4 | 2 | |m Digitalisierung UB Bamberg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016971148&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-016971148 | ||
Datensatz im Suchindex
| _version_ | 1804138328917803008 |
|---|---|
| adam_text | Contents
ACKNOWLEDGEMENTS
xv
PREFACE
xvii
CHAPTER
1
www.simulation: What, Why and
Whenľ
1
1.1
Introduction
.......................................... 1
1.2
What is simulation/
...................................... 2
1.3
Why simulate?
......................................... 4
1.3.1
The nature of operations systems: variability,
interconnectedness and complexity
..................... 4
1.3.2
The advantages of simulation
......................... 8
1.3.3
The disadvantages of simulation
........................ 10
1.4
When to simulate
....................................... 11
1.5
Conclusion
........................................... 11
Exercises
............................................. 12
References
............................................ 12
CHAPTER
2
Inside Simulation Software
13
2.1
Introduction
.......................................... 13
2.2
Modelling the progress of time
............................... 13
2.2.1
The time-slicing approach
........................... 14
2.2.2
The discrete-event simulation approach
(three-phase method)
.............................. 15
2.2.3
The continuous simulation approach
..................... 24
2.2.4
Summary: modelling the progress of time
.................. 26
2.3
Modelling variability
..................................... 26
2.3.1
Modelling unpredictable variability
...................... 26
_ [
viii
] --------------------------------------------------------------------------------------------------
Contents
2.3.2
Random numbers
................................. 26
2.3.3
Relating random numbers to variability in a simulation
......... 27
2.3.4
Modelling variability in times
......................... 27
2.3.5
Sampling from standard statistical distributions
.............. 30
2.3.6
Computer generated random numbers
.................... 31
2.3.7
Modelling predictable variability
....................... 33
2.3.8
Summary on modelling variability
...................... 33
2.4
Conclusion
........................................... 33
Exercises
............................................. 34
References
............................................ 35
CHAPTER
3
Software for Simulation
37
3.1
Introduction
.......................................... 37
3.2
Visual interactive simulation
................................ 38
3.3
Simulation software
...................................... 39
3.3.1
Spreadsheets
.................................... 39
3.3.2
Programming languages
............................. 40
3.3.3
Specialist simulation software
......................... 40
3.3.4
Comparing spreadsheets, programming languages and specialist
simulation software
................................ 41
3.4
Selection of simulation software
.............................. 43
3.4-1
The process of software selection
....................... 43
3.4-2
Step
1 :
Establish the modelling requirements
............... 44
3.4.3
Step
2:
Survey and shortlist the software
.................. 44
3.4-4
Step
3:
Establish evaluation criteria
..................... 44
3.4-5
Step
4:
Evaluate the software in relation to the criteria
......... 45
3.4.6
Step
5:
Software selection
............................ 46
3.5
Conclusion
........................................... 47
References
............................................ 48
CHAPTER
4
Simulation Studies: An Overview
51
41
Introduction
.......................................... 51
4.2
Simulation studies: an overview of key modelling processes
............ 51
4-2.1
Simulation modelling is not linear
...................... 54
4-2.2
Something is missing!
.............................. 55
4.3
Simulation project time-scales
............................... 56
4-4
The simulation project team
................................ 57
4-5
Hardware and software requirements
........................... 58
4-6
Project costs
........................................... 59
4-7
Project selection
........................................ 60
4-8
Conclusion
........................................... 61
References
............................................ 61
---------------------------------------------------------------------------------------------------- [ix] -
Contents
CHAPTER
5
Conceptual Modelling
63
5.1
Introduction
.......................................... 63
5.2
Conceptual modelling: important but little understood
............... 63
5.3
What is a conceptual model?
................................ 65
5.4
Requirements of the conceptual model
......................... 66
5.4.1
Four requirements of a conceptual model
.................. 66
5.4-2
Keep the model simple
.............................. 68
5.5
Communicating the conceptual model
.......................... 69
5.5.1
Simulation project specification
........................ 69
5.5.2
Representing the conceptual model
..................... 71
5.6
Conclusion
........................................... 74
Exercise
............................................. 74
References
............................................ 74
CHAPTER
6
Developing the Conceptual Model
77
6.1
Introduction
.......................................... 77
6.2
A Framework for conceptual modelling
......................... 77
6.2.1
Developing an understanding of the problem situation
......... 78
6.2.2
Determining the modelling objectives
.................... 80
6.2.3
Designing the conceptual model: the inputs and outputs
........ 82
6.2.4
Designing the conceptual model: the model content
........... 83
6.2.5
The role of data in conceptual modelling
.................. 85
6.2.6
Summary of the conceptual modelling framework
............ 86
6.3
Methods of model simplification
.............................. 87
6.3.1
Aggregation of model components
...................... 88
6.3.2
Excluding components and details
...................... 89
6.3.3
Replacing components with random variables
............... 89
6.3.4
Excluding infrequent events
.......................... 90
6.3.5
Reducing the rule set
............................... 90
6.3.6
Splitting models
.................................. 90
6.3.7
What is a good simplification?
......................... 91
6.4
Conclusion
........................................... 92
Exercises
............................................. 92
References
............................................ 93
CHAPTER
7
Data Collection and Analysis
95
7.1
Introduction
.......................................... 95
7.2
Data requirements
....................................... 95
7.3
Obtaining data
......................................... 97
7.3.1
Dealing with unobtainable (category C) data
............... 98
_
[χ]
---------------------------------------------------------------------------------------------------------------
Contents
7.3.2
Data accuracy
................................... 99
7.3.3
Data format
..................................... 99
7.4
Representing unpredictable variability
..........................100
7.4.1
Traces
........................................ 100
7.4-2
Empirical distributions
.............................. 101
7.4-3
Statistical distributions
.............................. 102
7.4-4
Traces versus empirical distributions versus statistical distributions
. 107
7.4-5
Bootstrapping
................................... 110
7.4.6
Further issues in representing unpredictable variability: correlation
and non-stationary data
............................. 110
7.5
Selecting statistical distributions
.............................
Ill
7.5.1
Selecting distributions from known properties of the process
..... 112
7.5.2
Fitting statistical distributions to empirical data
.............. 112
7.6
Conclusion
........................................... 121
Exercises
............................................. 121
References
............................................ 124
CHAPTER
8
Model Coding
127
8.1
Introduction
.......................................... 127
8.2
Structuring the model
.................................... 127
8.3
Coding the model
....................................... 128
8.3.1
Separate the data from the code from the results
............. 129
8.3.2
Use of
pseudo
random number streams
................... 130
8.4
Documenting the model and the simulation project
................. 133
8.5
Conclusion
............................................ 135
Exercises
............................................. 136
References
............................................ 136
CHAPTER
9
Experimentation: Obtaining Accurate Results
137
9.1
Introduction
.......................................... 137
9.2
The nature of simulation models and simulation output
............... 137
9.2.1
Terminating and non-terminating simulations
.............. 138
9.2.2
Transient output
.................................. 138
9.2.3
Steady-state output
................................ 138
9.2.4
Other types of output
............................... 140
9.2.5
Determining the nature of the simulation output
............. 140
9.3
Issues in obtaining accurate simulation results
..................... 141
9.3.1
Initialization bias: warm-up and initial conditions
............ 141
9.3.2
Obtaining sufficient output data: long runs and multiple replications
142
9.4
An example model: computer user help desk
...................... 142
9.5
Dealing with initialization bias: warm-up and initial conditions
.......... 143
9.5.1
Determining the warm-up period
....................... 143
--------------------------------------------------------------------------------------------------------------------------- [Xi] .
Contents
9.5.2
Setting initial conditions
............................ 150
9.5.3
Mixed initial conditions and warm-up
.................... 150
9.5.4
Initial conditions versus warm-up
....................... 151
9.6
Selecting the number of replications and run-length
................. 151
9.6.1
Performing multiple replications
....................... 152
9.6.2
Variance reduction (antithetic
variâtes)
................... 157
9.6.3
Performing a single long run
.......................... 159
9.6.4
Multiple replications versus long runs
.................... 162
9.7
Conclusion
........................................... 163
Exercises
............................................. 163
References
............................................ 167
CHAPTER
10
Experimentation: Searching the Solution Space
169
10.1
Introduction
.......................................... 169
10.2
The nature of simulation experimentation
....................... 171
10.2.1
Interactive and batch experimentation
................... 171
10.2.2
Comparing alternatives and search experimentation
........... 172
10.3
Analysis of results from a single scenario
........................ 173
10.3.1
Point estimates
................................... 173
10.3.2
Measures of variability
.............................. 176
10.4
Comparing alternatives
................................... 177
10.4-1
Comparison of two scenarios
.......................... 178
10.4-2
Comparison of many scenarios
......................... 180
10.4-3
Choosing the best
scenario(s)
......................... 183
10.5
Search experimentation
................................... 183
10.5.1
Informal approaches to search experimentation
.............. 184
10.5.2
Experimental design
............................... 186
10.5.3
Metamodelling
................................... 190
10.5.4
Optimization ( searchization )
........................ 192
10.6
Sensitivity analysis
...................................... 194
10.7
Conclusion
........................................... 195
Exercises
............................................. 196
References
............................................ 198
CHAPTER
11
Implementation
201
11.1
Introduction
.......................................... 201
11.2
What is implementation?
.................................. 201
11.2.1
Implementing the findings
........................... 201
11.2.2
Implementing the model
............................ 202
11.2.3
Implementation as learning
........................... 203
11.3
Implementation and simulation project success
.................... 203
11.3.1
What is simulation project success?
...................... 204
-
[хи]
--------------------------------------------------------------------------------------------------------------------------------
Contents
11.3.2
How is success achieved/
............................ 204
11.3.3
How is success measured/
............................ 206
11.4
Conclusion
........................................... 207
References
............................................ 207
CHAPTER
12
Verification, Validation and Confidence
209
12.1
Introduction
.......................................... 209
12.2
What is verification and validation?
........................... 209
12.3
The difficulties of verification and validation
...................... 212
12.3.1
There is no such thing as general validity
.................. 213
12.3.2
There may be no real world to compare against
.............. 213
12.3.3
Which real
worldľ
................................. 213
12.3.4
Often the real world data are inaccurate
................... 213
12.3.5
There is not enough time to verify and validate everything
...... 214
12.3.6
Confidence not validity
............................. 214
12.4
Methods of verification and validation
.......................... 214
12.4.1
Conceptual model validation
.......................... 214
12.4-2
Data validation
.................................. 215
12.4.3
Verification and white-box validation
.................... 215
12.4.4
Black-box validation
............................... 217
12.4-5
Experimentation validation
........................... 220
12.4-6
Solution validation
................................ 220
12.5
Independent verification and validation
......................... 221
12.6
Conclusion
........................................... 222
Exercises
............................................. 223
References
............................................ 224
CHAPTER
13
The Practice of Simulation
227
13.1
Introduction
.......................................... 227
13.2
Types of simulation model
................................. 227
13.3
Modes of simulation practice
................................ 230
13.3.1
Three modes of practice
............................. 230
13.3.2
Facets of the modes of simulation practice
................. 231
13.3.3
Modes of practice in business and the military
............... 233
13.4
Conclusion
........................................... 235
References
............................................ 235
APPENDIX
1: Wardeon
Cinema
237
APPENDIX
2:
Panorama Televisions
259
APPENDIX
3:
Methods of reporting simulation results
279
-------------------------------------------------------------------------------------------------------------------------------------------------- [ Xiii ]
Contents
APPENDIX
4:
Statistical distributions
289
APPENDIX
5:
Critical values for the chi-square test
301
APPENDIX
6:
Critical values for the Student s t-distribution
303
Index
305
|
| adam_txt |
Contents
ACKNOWLEDGEMENTS
xv
PREFACE
xvii
CHAPTER
1
www.simulation: What, Why and
Whenľ
1
1.1
Introduction
. 1
1.2
What is simulation/
. 2
1.3
Why simulate?
. 4
1.3.1
The nature of operations systems: variability,
interconnectedness and complexity
. 4
1.3.2
The advantages of simulation
. 8
1.3.3
The disadvantages of simulation
. 10
1.4
When to simulate
. 11
1.5
Conclusion
. 11
Exercises
. 12
References
. 12
CHAPTER
2
Inside Simulation Software
13
2.1
Introduction
. 13
2.2
Modelling the progress of time
. 13
2.2.1
The time-slicing approach
. 14
2.2.2
The discrete-event simulation approach
(three-phase method)
. 15
2.2.3
The continuous simulation approach
. 24
2.2.4
Summary: modelling the progress of time
. 26
2.3
Modelling variability
. 26
2.3.1
Modelling unpredictable variability
. 26
_ [
viii
] --------------------------------------------------------------------------------------------------
Contents
2.3.2
Random numbers
. 26
2.3.3
Relating random numbers to variability in a simulation
. 27
2.3.4
Modelling variability in times
. 27
2.3.5
Sampling from standard statistical distributions
. 30
2.3.6
Computer generated random numbers
. 31
2.3.7
Modelling predictable variability
. 33
2.3.8
Summary on modelling variability
. 33
2.4
Conclusion
. 33
Exercises
. 34
References
. 35
CHAPTER
3
Software for Simulation
37
3.1
Introduction
. 37
3.2
Visual interactive simulation
. 38
3.3
Simulation software
. 39
3.3.1
Spreadsheets
. 39
3.3.2
Programming languages
. 40
3.3.3
Specialist simulation software
. 40
3.3.4
Comparing spreadsheets, programming languages and specialist
simulation software
. 41
3.4
Selection of simulation software
. 43
3.4-1
The process of software selection
. 43
3.4-2
Step
1 :
Establish the modelling requirements
. 44
3.4.3
Step
2:
Survey and shortlist the software
. 44
3.4-4
Step
3:
Establish evaluation criteria
. 44
3.4-5
Step
4:
Evaluate the software in relation to the criteria
. 45
3.4.6
Step
5:
Software selection
. 46
3.5
Conclusion
. 47
References
. 48
CHAPTER
4
Simulation Studies: An Overview
51
41
Introduction
. 51
4.2
Simulation studies: an overview of key modelling processes
. 51
4-2.1
Simulation modelling is not linear
. 54
4-2.2
Something is missing!
. 55
4.3
Simulation project time-scales
. 56
4-4
The simulation project team
. 57
4-5
Hardware and software requirements
. 58
4-6
Project costs
. 59
4-7
Project selection
. 60
4-8
Conclusion
. 61
References
. 61
---------------------------------------------------------------------------------------------------- [ix] -
Contents
CHAPTER
5
Conceptual Modelling
63
5.1
Introduction
. 63
5.2
Conceptual modelling: important but little understood
. 63
5.3
What is a conceptual model?
. 65
5.4
Requirements of the conceptual model
. 66
5.4.1
Four requirements of a conceptual model
. 66
5.4-2
Keep the model simple
. 68
5.5
Communicating the conceptual model
. 69
5.5.1
Simulation project specification
. 69
5.5.2
Representing the conceptual model
. 71
5.6
Conclusion
. 74
Exercise
. 74
References
. 74
CHAPTER
6
Developing the Conceptual Model
77
6.1
Introduction
. 77
6.2
A Framework for conceptual modelling
. 77
6.2.1
Developing an understanding of the problem situation
. 78
6.2.2
Determining the modelling objectives
. 80
6.2.3
Designing the conceptual model: the inputs and outputs
. 82
6.2.4
Designing the conceptual model: the model content
. 83
6.2.5
The role of data in conceptual modelling
. 85
6.2.6
Summary of the conceptual modelling framework
. 86
6.3
Methods of model simplification
. 87
6.3.1
Aggregation of model components
. 88
6.3.2
Excluding components and details
. 89
6.3.3
Replacing components with random variables
. 89
6.3.4
Excluding infrequent events
. 90
6.3.5
Reducing the rule set
. 90
6.3.6
Splitting models
. 90
6.3.7
What is a good simplification?
. 91
6.4
Conclusion
. 92
Exercises
. 92
References
. 93
CHAPTER
7
Data Collection and Analysis
95
7.1
Introduction
. 95
7.2
Data requirements
. 95
7.3
Obtaining data
. 97
7.3.1
Dealing with unobtainable (category C) data
. 98
_
[χ]
---------------------------------------------------------------------------------------------------------------
Contents
7.3.2
Data accuracy
. 99
7.3.3
Data format
. 99
7.4
Representing unpredictable variability
.100
7.4.1
Traces
. 100
7.4-2
Empirical distributions
. 101
7.4-3
Statistical distributions
. 102
7.4-4
Traces versus empirical distributions versus statistical distributions
. 107
7.4-5
Bootstrapping
. 110
7.4.6
Further issues in representing unpredictable variability: correlation
and non-stationary data
. 110
7.5
Selecting statistical distributions
.
Ill
7.5.1
Selecting distributions from known properties of the process
. 112
7.5.2
Fitting statistical distributions to empirical data
. 112
7.6
Conclusion
. 121
Exercises
. 121
References
. 124
CHAPTER
8
Model Coding
127
8.1
Introduction
. 127
8.2
Structuring the model
. 127
8.3
Coding the model
. 128
8.3.1
Separate the data from the code from the results
. 129
8.3.2
Use of
pseudo
random number streams
. 130
8.4
Documenting the model and the simulation project
. 133
8.5
Conclusion
. 135
Exercises
. 136
References
. 136
CHAPTER
9
Experimentation: Obtaining Accurate Results
137
9.1
Introduction
. 137
9.2
The nature of simulation models and simulation output
. 137
9.2.1
Terminating and non-terminating simulations
. 138
9.2.2
Transient output
. 138
9.2.3
Steady-state output
. 138
9.2.4
Other types of output
. 140
9.2.5
Determining the nature of the simulation output
. 140
9.3
Issues in obtaining accurate simulation results
. 141
9.3.1
Initialization bias: warm-up and initial conditions
. 141
9.3.2
Obtaining sufficient output data: long runs and multiple replications
142
9.4
An example model: computer user help desk
. 142
9.5
Dealing with initialization bias: warm-up and initial conditions
. 143
9.5.1
Determining the warm-up period
. 143
--------------------------------------------------------------------------------------------------------------------------- [Xi] .
Contents
9.5.2
Setting initial conditions
. 150
9.5.3
Mixed initial conditions and warm-up
. 150
9.5.4
Initial conditions versus warm-up
. 151
9.6
Selecting the number of replications and run-length
. 151
9.6.1
Performing multiple replications
. 152
9.6.2
Variance reduction (antithetic
variâtes)
. 157
9.6.3
Performing a single long run
. 159
9.6.4
Multiple replications versus long runs
. 162
9.7
Conclusion
. 163
Exercises
. 163
References
. 167
CHAPTER
10
Experimentation: Searching the Solution Space
169
10.1
Introduction
. 169
10.2
The nature of simulation experimentation
. 171
10.2.1
Interactive and batch experimentation
. 171
10.2.2
Comparing alternatives and search experimentation
. 172
10.3
Analysis of results from a single scenario
. 173
10.3.1
Point estimates
. 173
10.3.2
Measures of variability
. 176
10.4
Comparing alternatives
. 177
10.4-1
Comparison of two scenarios
. 178
10.4-2
Comparison of many scenarios
. 180
10.4-3
Choosing the best
scenario(s)
. 183
10.5
Search experimentation
. 183
10.5.1
Informal approaches to search experimentation
. 184
10.5.2
Experimental design
. 186
10.5.3
Metamodelling
. 190
10.5.4
Optimization ("searchization")
. 192
10.6
Sensitivity analysis
. 194
10.7
Conclusion
. 195
Exercises
. 196
References
. 198
CHAPTER
11
Implementation
201
11.1
Introduction
. 201
11.2
What is implementation?
. 201
11.2.1
Implementing the findings
. 201
11.2.2
Implementing the model
. 202
11.2.3
Implementation as learning
. 203
11.3
Implementation and simulation project success
. 203
11.3.1
What is simulation project success?
. 204
-
[хи]
--------------------------------------------------------------------------------------------------------------------------------
Contents
11.3.2
How is success achieved/
. 204
11.3.3
How is success measured/
. 206
11.4
Conclusion
. 207
References
. 207
CHAPTER
12
Verification, Validation and Confidence
209
12.1
Introduction
. 209
12.2
What is verification and validation?
. 209
12.3
The difficulties of verification and validation
. 212
12.3.1
There is no such thing as general validity
. 213
12.3.2
There may be no real world to compare against
. 213
12.3.3
Which real
worldľ
. 213
12.3.4
Often the real world data are inaccurate
. 213
12.3.5
There is not enough time to verify and validate everything
. 214
12.3.6
Confidence not validity
. 214
12.4
Methods of verification and validation
. 214
12.4.1
Conceptual model validation
. 214
12.4-2
Data validation
. 215
12.4.3
Verification and white-box validation
. 215
12.4.4
Black-box validation
. 217
12.4-5
Experimentation validation
. 220
12.4-6
Solution validation
. 220
12.5
Independent verification and validation
. 221
12.6
Conclusion
. 222
Exercises
. 223
References
. 224
CHAPTER
13
The Practice of Simulation
227
13.1
Introduction
. 227
13.2
Types of simulation model
. 227
13.3
Modes of simulation practice
. 230
13.3.1
Three modes of practice
. 230
13.3.2
Facets of the modes of simulation practice
. 231
13.3.3
Modes of practice in business and the military
. 233
13.4
Conclusion
. 235
References
. 235
APPENDIX
1: Wardeon
Cinema
237
APPENDIX
2:
Panorama Televisions
259
APPENDIX
3:
Methods of reporting simulation results
279
-------------------------------------------------------------------------------------------------------------------------------------------------- [ Xiii ]
Contents
APPENDIX
4:
Statistical distributions
289
APPENDIX
5:
Critical values for the chi-square test
301
APPENDIX
6:
Critical values for the Student's t-distribution
303
Index
305 |
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| index_date | 2024-07-02T22:51:51Z |
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| institution | BVB |
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| spelling | Robinson, Stewart Verfasser aut Simulation the practice of model development and use Stewart Robinson Reprint. Chichester [u.a.] Wiley 2007 XIX, 316 S. Ill., graph. Darst. 24 cm txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index aComputer simulation aSimulation methods Modellierung (DE-588)4170297-9 gnd rswk-swf Computersimulation (DE-588)4148259-1 gnd rswk-swf Computersimulation (DE-588)4148259-1 s Modellierung (DE-588)4170297-9 s DE-604 http://www.loc.gov/catdir/bios/wiley045/2003063093.html Contributor biographical information http://www.loc.gov/catdir/description/wiley041/2003063093.html Publisher description http://www.loc.gov/catdir/toc/wiley041/2003063093.html Table of contents Digitalisierung UB Bamberg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016971148&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Simulation the practice of model development and use |
| title_auth | Simulation the practice of model development and use |
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| title_short | Simulation |
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