Modelling in Natural Sciences: Design, Validation and Case Studies

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Springer Science & Business Media, Feb 14, 2003 - Computers - 459 pages
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Zwar weifl ich viei, doch macht' ich alles wissen 1 Goethe, Faust 1, Vers 601 Man has always recognized his limitations as a challenge to strive for new hori zons. Today, technical progress enables him to realize this ambition; one of the means are models granting new insights into phenomena or problems which can not be observed or (otherwise) explained. Depending on the standpoint of the ex pert, the model is either mainly retrospective - like Darwin's theory of natural selection as a model to explain the evolution of species - or it concentrates pro spectiveiy on the future by trying to predict events, e. g. catastrophes such as floods or droughts. Naturally, all these models are not perfect as they are man made, but they do help to solve problems. Politicians should draw consequences from these observations; but as they cannot be expected to evaluate such models, they need highly qualified advisers. This exposition already indicates that the terrn model encompasses many dif ferent facets with far-reaching consequences. We quote several examples in order to demonstrate the rather indefmite interpretation of the terrn and the various pur poses models are to serve; in fact we come to the conclusion that there are literally 'models everywhere'. Diverse as models are, they all share some common ideas such as the structural aspects of the modelling process.
  

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Contents

Models
1
12 Etyma
31
13 Purposes
34
Systems
46
22 Characterizing Systems
49
23 Dynamic Systems
63
24 Systems Analysis
72
Mappings
97
Tolerance
228
82 The Quantitative Aspect
234
Tests
237
92 Terminology
239
93 Testing
242
Validity
249
101 Validation
250
102 The Scope
251

32 Structure Preservation
100
33 Chains and Invariants
107
34 Morphisms
111
Characterizing Models
120
41 Contents
121
42 Selection
127
43 Projection
134
The Art of Modelling
139
51 Creating a Model
142
52 Quality Criteria
159
Inferences
169
61 Deductive Inference
171
62 Inductive Inference
179
63 Personal Inference
191
Probabilities
195
72 Inductive Stochastic Inference
198
73 Certainty and Prior Probability
223
103 Epistemic Foundations
257
104 Quantifying the Validity of a Model
260
105 Evaluating a Model
265
Suggestions for Further Reading
267
References
269
Appendix
275
Modelling the Evolution of Galaxies
279
Model Environments for an Early Alkaline Ocean
309
Reconstructing the development of paleospecies
323
The Modau Case Study
335
Physical Modeling of a Glass Melter
357
Modelling of Complexation Equilibria
379
Weather Prediction by Numerical Modelling of Atmospheric Processes
413
Simulation of Hydrogen Behaviour During a Nuclear Power Plant Accident
435
List of Contributors
457
Copyright

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