基于CA和AR方法的连续状态空间场动态演化模拟

Modeling dynamic evolution of continual state spatial field based on CA and AR method

为了预测连续状态属性在地理空间场中的变化趋势,本文在CA和AR方法的基础上,构建了模拟连续状态空间场动态演化的CA-AR模型。提出了预测连续状态属性的CA-AR概念模型以及具体的表达形式。对模型的应用流程进行了说明,即:数据预处理→空间场的栅格化→属性数据导入→模型参数估计→模型显著性检验五个步骤。研究表明,CA-AR模型在理论上是可行的,具有进一步实践的价值。

In order to forecast the trend of continual state attribute in the geographic spatial field, CA-AR model was set up to simulate the dynamic evolution of continual state spatial field based on CA and AR method. The concept model and material expressions was put forward which can forecast the continual state attribute. The application flow was explained as the following five steps: data pretreatment, spatial field rasterization, attribute importing, model parameters estimation, and model verifying. It was indicated that the model was feasible theoretically and would have the further practice value.