Dynamic Models and Discrete Event Simulation
eBook - ePub

Dynamic Models and Discrete Event Simulation

  1. 672 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Dynamic Models and Discrete Event Simulation

About this book

This book aims to clarify exactly how simulation studies can be carried out in the system theory paradigm, while providing a realistically complete coverage of (discrete event) simulation in its more traditional aspects. It focuses on the subclass of predictive, generative and dynamic system models.

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Yes, you can access Dynamic Models and Discrete Event Simulation by W. Delaney in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Electrical Engineering & Telecommunications. We have over one million books available in our catalogue for you to explore.
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Table of contents

  1. Cover
  2. Half Title
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Preface
  7. Contents
  8. 1 Systems and Models
  9. I. Introduction
  10. III. Experiments
  11. IV. Models
  12. V. Summary
  13. Appendix: Example of An Open System
  14. References
  15. Problems
  16. 2 Deterministic Models
  17. I. Introduction
  18. III. Vector-Matrix Formulation
  19. IV. General Solution Methods
  20. V. Equilibrium and Stability
  21. VI. Nonparametric Models
  22. VII. Analytic Approximation Methods
  23. VIII. Numerical Approximation Methods
  24. IX. Error Considerations
  25. X. Identification of Deterministic Models
  26. XI. Summary
  27. Appendix: Vector-Matrix Formalism
  28. References
  29. Problems
  30. 3 Stochastic Models
  31. I. Introduction
  32. III. Joint and Conditional PFs and Moments
  33. IV. Vector-Matrix Notation for RVs
  34. V. Stochastic Processes
  35. VI. SP Models
  36. VII. Generative Stochastic System Models
  37. VIII. Probability Function Models
  38. IX. Summary
  39. References
  40. Problems
  41. 4 Identification of Stochastic Systems
  42. II. Estimation of Probabilities and Moments
  43. III. Stochastic Model Identification
  44. IV. Summary
  45. Appendix A
  46. Appendix B
  47. References
  48. Problems
  49. 5 Modeling of Complex Systems
  50. I. Introduction
  51. III. Simulation Models
  52. IV. System Analysis, Submodel Identification, and Model Synthesis
  53. V. Simulation as Experimentation
  54. VI. Simulation Purposes
  55. VIII. Methodological Aspects
  56. IX. Summary
  57. References
  58. Problems
  59. 6 The Experimental Aspect of Simulation
  60. II. Experimentation
  61. III. Analogies between Real and Simulated Experiments
  62. IV. Simulated Experiments
  63. V. Validation of Experimental Design
  64. VII. A Case Study
  65. References
  66. Problems
  67. 7 The Modeling Aspect of Simulation
  68. I. Introduction
  69. III. Simulation Model Content
  70. IV. Model Validation
  71. V. Summary
  72. Appendix: Simulated Sampling
  73. References
  74. Problems
  75. 8 The Programming Aspect of Simulation
  76. I. Introduction
  77. III. Environments
  78. IV. Validation
  79. V. Summary
  80. References
  81. Problems
  82. 9 Future Trends in Modeling and Simulation
  83. I. Introduction
  84. III. The Problems of Validity and Completeness
  85. IV. Ease of Realization and Use
  86. V. Summary
  87. References
  88. Problems
  89. 10 Simulation Examples
  90. II. A Disk Drive Simulation
  91. III. A Hospital Simulation
  92. IV. A Nuclear Physics Experiment
  93. V. Summary
  94. References
  95. Table of Mnemonic Names
  96. Index