基于Petri网的模型与GIS集成研究

以BP神经网络遥感分类模型为例，探讨了模型与地理信息系统的集成问题，指出问题的实质是对象状态数据模型，对象模拟模型和对象分析处理模型的综合表达与处理，提出了建立在元数据和元模型基础上基于数据处理的流程的集成方案的一般结构，分析了Petri网的演泽形Derivation网的特点，设计了Derivation 网，提出了Derivation 网对元数据和元模型的管理方案以及Derivation 网内部校验方法，在此基础上以Derivation 网为核心，以元数据和元模型为接口，建立了基于数据处理流程的模型与GIS的集成方案。

Integration of Model and GIS Based on Petri Nets

This paper discussed the integration of model and GIS. It is shown that the integrated expression and the processes of the object state model, the object simulative model and the object analytic model are key issues for integration. An integration scheme based on metadata and metamodel is suggested. The characteristic of the derivation nets deducted from petri nets was analyzed and a new derivation nets was presented to express the evolution history of metadata and the adjustment of metamodel. Then an integration scheme based on derivation nets, which is used to express the data process flow, was proposed. As a result, a derivation net of the remote sensing classifier of BP neural nets is made to illustrate the strategy of the integration of model and GIS.