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      Study on Validation Method of Simulation Model Combination

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      https://www.riss.kr/link?id=A101827509

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      다국어 초록 (Multilingual Abstract)

      Aimed at improving the efficiency of the development of complex simulation system and the problem of lower development costs, a validation development framework is proposed based on combination model. The system development process can be broken in the discovery of decomposition for the model, combination and combination of validation phase. This thesis gives the validation method based on model of tag transfer system behavior, judging by strong simulation and semantic similarity relations after the combination model of dynamic behavior and request model conforms to the degree. Simulation model combined the experimental results show that the method can automatically finish the combination of the simulation model validation, the validity of the model validation can meet the requirements of practical application.
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      Aimed at improving the efficiency of the development of complex simulation system and the problem of lower development costs, a validation development framework is proposed based on combination model. The system development process can be broken in th...

      Aimed at improving the efficiency of the development of complex simulation system and the problem of lower development costs, a validation development framework is proposed based on combination model. The system development process can be broken in the discovery of decomposition for the model, combination and combination of validation phase. This thesis gives the validation method based on model of tag transfer system behavior, judging by strong simulation and semantic similarity relations after the combination model of dynamic behavior and request model conforms to the degree. Simulation model combined the experimental results show that the method can automatically finish the combination of the simulation model validation, the validity of the model validation can meet the requirements of practical application.

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      목차 (Table of Contents)

      • Abstract
      • 1. Introduction
      • 2. Model Development Framework
      • 2.1. The Key Variables and Indicators of Statistical Analysis Methods
      • 2.2. The Analysis of Continuous Dynamic Process Consistency
      • Abstract
      • 1. Introduction
      • 2. Model Development Framework
      • 2.1. The Key Variables and Indicators of Statistical Analysis Methods
      • 2.2. The Analysis of Continuous Dynamic Process Consistency
      • 2.3. Discrete Event Validation
      • 2.4. Mixed Behavior
      • 3. Dynamic Behavior Model Validation
      • 3.1. Simulation Model Matching
      • 3.2. Method Validation Process
      • 4. The Simulation Model Representation
      • 4.1. Static Data Characteristic Difference Model
      • 4.2. Graded Data Characteristic Difference Measurement Model
      • 5. Combination Model’s Inspection
      • 5.1. Improvement of Periodogram Estimation
      • 5.2. The Test Method of Wavelet
      • 6. Validation Method Instance
      • 7. Conclusion
      • References
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