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基于空间数据挖掘的分区异步元胞自动机模型研究

DOI: 10.11834/jig.20100611

Keywords: 元胞自动机,空间数据挖掘,分区,异步

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Abstract:

传统的元胞自动机模型采用统一的转换规则和相同的演化速率进行演化,忽略了地理现象演变的时空差异性:演化规律的空间异质性和演化速率的空间差异性。针对这一问题,提出了基于空间数据挖掘的分区异步元胞自动机模型,采用双约束空间聚类的方法对元胞空间进行分区,用分区转换规则替代统一转换规则可以体现地理现象演化规律的空间差异性;采用标准格网划分的方法求取异步元胞演化速率,用异步演化速率替代同步演化速率可以体现地理现象演化速率的空间差异性。以杭州市土地利用变化为例对基于空间数据挖掘的分区异步元胞自动机模型进行了实证研究,结果表明:与传统的元胞自动机模型相比,基于空间数据挖掘的分区异步元胞自动机模型具有较高的模拟精度,并且适用于较大区域较长时间段地理现象的动态变化模拟。基于空间数据挖掘的分区异步元胞自动机模型是地理元胞自动机研究的新视角,它将地理现象演变的空间异质性和时间差异性引入到地理元胞自动机模型中,使模型对地理过程的模拟更接近实际地理过程。然而,由于有关分区异步的元胞自动机模型还处于尝试性研究阶段,在元胞空间分区方法、双约束空间聚类算法中权重的确定方法、元胞演化速率的获取方法、元胞转换规则的获取方法、模拟精度评估以及分区异步元胞自动机模型在较大区域较长时间的地理现象模拟中的应用等方面有待进一步的研究与探讨。

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