Knowledge-based modeling of discrete-event simulation systems

H. D. S. Arons
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引用次数: 7

Abstract

Modeling a simulation system requires a great deal of customization. At first sight no system seems to resemble exactly another system and every time a new model has to be designed the modeler has to start from scratch. The present simulation languages provide the modeler with powerful tools that greatly facilitate building models (modules for arrivals or servers, etc.). Yet, also with these tools the modeler constantly has the feeling that he is reinventing the wheel again and again. Maybe the model he is about to design already exists (maybe the modeler has designed it himself some time ago) or maybe a model already exists that sufficiently resembles the model to be designed. In this article an approach is discussed that deploys knowledge-based systems to help selecting a model from a database of existing models. Also, if the model is not present in the database, would it be possible to select a model that in some sense is close to the model that the modeler had in mind?.
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离散事件仿真系统的知识建模
对仿真系统进行建模需要进行大量的定制。乍一看,没有一个系统看起来与另一个系统完全相似,每次设计一个新模型时,建模者都必须从头开始。目前的仿真语言为建模者提供了强大的工具,极大地促进了模型的构建(到达或服务器的模块等)。然而,也与这些工具建模不断有感觉,他是重新发明轮子一次又一次。也许他将要设计的模型已经存在(也许建模者自己在一段时间以前设计过),或者可能已经存在一个与要设计的模型足够相似的模型。本文讨论了一种部署基于知识的系统来帮助从现有模型的数据库中选择模型的方法。另外,如果模型不存在于数据库中,是否有可能选择一个在某种意义上接近建模者所考虑的模型的模型?
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