Domain-specific decision modelling and statistical analysis for combat system effectiveness simulation.
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| Titel: | Domain-specific decision modelling and statistical analysis for combat system effectiveness simulation. |
|---|---|
| Autoren: | Li, Xiaobo, Lei, Yonglin, Vangheluwe, Hans, Wang, Weiping, Li, Qun |
| Quelle: | Journal of Statistical Computation & Simulation; Jun2014, Vol. 84 Issue 6, p1261-1279, 19p |
| Schlagwörter: | STATISTICS, SIMULATION methods & models, DECISION making, QUANTITATIVE research, MATHEMATICAL optimization, DOMAIN-specific programming languages, PYTHON programming language, BAYESIAN analysis, PARAMETER estimation |
| Abstract: | Combat system effectiveness simulation (CoSES) needs to model both the physical aspect (i.e. physics modelling) and intelligent aspect (i.e. decision modelling) of combat systems. Combat platform decision-making has several characteristics such as cognition, diversity, agility, uncertainty and higher abstraction level, which bring tough challenges for decision model design, implementation and optimization. In this paper, we propose a domain-specific modelling approach which develops friendly modelling environments for model design, we design code generation mechanisms to transform domain-specific decision models to Python code which is supported by a Python script framework to implement decision models and we present a Bayesian network-based statistical analysis method on simulation output data to optimize the decision model. The case study shows that the proposed modelling and optimization approach effectively supports CoSES with decision models of higher efficiency and increased effectiveness. [ABSTRACT FROM AUTHOR] |
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| Datenbank: | Complementary Index |
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