Abstract: For the traditional model validation methods, the completeness is weak and it depends on human experience. The signed directed graph (SDG) and qualitative trend based model semiquantitative validation is proposed. First, the SDG model is built and qualitative trends are added to the model. Then complete testing cases are produced by positive inference. The semiquantitative validation is carried out by comparing the testing cases with outputs of the simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.

Key words: imulation &, modeling, model validation, signed directed graph, qualitative trend

摘要： 针对传统仿真模型验证方法存在的完备性不足、过于依赖人经验等问题，提出一种基于符号有向图（Signed Directed Graph, SDG）与定性趋势的仿真模型半定量验证方法。该方法首先建立过程对象的SDG验证模型，并将定性趋势加入到模型中，然后通过正向推理产生完备的验证测试案例，同时在多个尺度分析比较测试案例与仿真模型输出的相似程度，实现了对仿真模型的半定量验证。最后采用一个反应器仿真模型进行案例研究，证明了方法的有效性。

关键词: 仿真建模, 模型验证, 符号有向图, 定性趋势