Elsevier S & T

Systems Analysis and Modeling: A Macro-to-Micro Approach with Multidisciplinary Applications

Boyd, Donald W.

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Table of contents
  • Contentsv
  • Prefaceix
  • Part I: Introduction to Analysis and Modeling1
  • Chapter 1. Systems Analysis and Model Synthesis3
  • 1.1 Introduction3
  • 1.2 Threefold Nature of the Universe5
  • 1.3 Entropy: Agent of Change10
  • 1.4 Hierarchical Analysis13
  • 1.5 Macro-to-Micro Analysis17
  • 1.6 Analytical Approaches19
  • 1.7 Comparison of Analytical Approaches28
  • Exercises32
  • Chapter 2. Systems Modeling Principles35
  • 2.1 Knowledge-Based Modeling35
  • 2.2 Circumscription Principle36
  • 2.3 Conservation Principle38
  • 2.4 Correspondence Principle39
  • 2.5 Classification of Model Variables39
  • 2.6 Linear Relationships42
  • 2.7 Time Series45
  • 2.8 Calibration Principles46
  • 2.9 Building-Block Principle49
  • 2.10 Exogenous Dynamic Forms51
  • 2.11 Endogenous Dynamic Forms52
  • 2.12 Information Feedback66
  • 2.13 Distortion Reduction66
  • Exercises69
  • Chapter 3. Population Model: Calibration and Validation75
  • 3.1 Introduction75
  • 3.2 Population Knowledge Base76
  • 3.3 Calibration of Population Model78
  • 3.4 Validation81
  • 3.5 Validation of Population Model84
  • 3.6 Error Control88
  • Exercises90
  • Appendix A94
  • Part II: Deterministic Models101
  • Chapter 4. Modeling with Dynamic Forms103
  • 4.1 Harmonic Oscillation Model103
  • 4.2 Polynomial Models113
  • Exercises125
  • Appendix B127
  • Chapter 5. Small Arms Exterior Ballistics Model129
  • 5.1 Projectile Knowledge Base130
  • 5.2 Calibration of Ballistics Model134
  • 5.3 Verification and Validation of Model139
  • 5.4 Conclusion and Discussion143
  • Exercises145
  • Appendix C147
  • Chapter 6. Inventory Systems Models: Shaping Dynamic Response149
  • 6.1 Inventory Accumulation Model149
  • 6.2 Inventory Reduction Model152
  • 6.3 Model of an Ideal Inventory System154
  • 6.4 Order Delay Model159
  • 6.5 Random Demand Model162
  • 6.6 Order Policy Model168
  • 6.7 Three-Policy Model171
  • Exercises175
  • Appendix D179
  • Chapter 7. Modeling Corporate Assets185
  • 7.1 Introduction185
  • 7.2 Asset Growth Model186
  • 7.3 Corporate Assets Planning Model192
  • Exercises204
  • Appendix E206
  • Part III: Stochastic Models209
  • Chapter 8. Stochastic Analysis211
  • 8.1 Introduction211
  • 8.2 Stochastic Representation212
  • 8.3 Modeling Stochastic Processes215
  • 8.4 Trend Analysis219
  • 8.5 Knowledge Acquisition via Inference Matrix222
  • 8.6 Regression Analysis224
  • Exercises225
  • Chapter 9. Work Physiology Model229
  • 9.1 Introduction229
  • 9.2 Systems Analysis231
  • 9.3 Knowledge Base231
  • 9.4 Generic Model233
  • 9.5 Calibration and Validation235
  • 9.6 Conclusions and Comments245
  • Exercises246
  • Appendix F248
  • Chapter 10. Macro Model of Blue Glacier255
  • 10.1 Introduction255
  • 10.2 Systems Analysis of Blue Glacier256
  • 10.3 Knowledge Base256
  • 10.4 Calibration258
  • 10.5 Model Validation260
  • 10.6 Static Relationships262
  • 10.7 Further Modeling265
  • Exercises265
  • Appendix G267
  • Chapter 11. State Water Planning Model269
  • 11.1 Introduction269
  • 11.2 Systems Analysis of Yellowstone River Basin272
  • 11.3 Knowledge Base273
  • 11.4 Calibration277
  • 11.5 Model Validation283
  • Exercises290
  • Appendix H292
  • Chapter 12. Prototyping A Forest Systems Model301
  • 12.1 Introduction301
  • 12.2 Knowledge Base303
  • 12.3 Calibration308
  • 12.4 Model Validation313
  • 12.5 Concluding Remarks320
  • Exercises321
  • Appendix I323
  • Chapter 13. Applications Unlimited325
  • 13.1 Introduction325
  • 13.2 Virtual Manufacturing325
  • 13.3 Time Series Synthesis331
  • 13.4 Optimization338
  • 13.5 Large-Scale Systems340
  • Exercises342
  • Appendix J344
  • References347
  • Glossary351
  • Index361
Book details
  • Vendor Elsevier S & T
  • SKU 9780121218515
  • ISBN-13 9780080518398
  • Author Boyd, Donald W.
  • Category Science
  • Subject System Theory

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Description eBook delivery & access Reviews
This book presents a fresh, new approach to systems analysis and modeling with a systems science flavor that stimulates systems thinking. After introducing systems modeling principles, the ensuing wide selection of examples aptly illustrate that anything which changes over time can be modeled as a system. Each example begins with a knowledge base that displays relevant information obtained from systems analysis. The diversity of examples clearly establishes a new protocol for synthesizing systems models.

* Macro-to-micro, top-down approach
* Multidisciplinary examples
* Incorporation of human knowledge to synthesise a systems model
* Clear and concise systems delimitation
* Complex systems using simple mathematics
* "Exact" reproduction of historical data plus model generated secondary data
* Systems simulation via systems models