【摘要】 提出了一种利用改进的最短距离算法自动获取地理元胞自动机转换规则的方法。CA的核心是如何定义转换规则,但目前主要是采用启发式的方法来定义转换规则,受主观因素影响较大。该模型通过熵化空间变量特征权重,对最短距离算法进行改进,自动获取CA的转换规则和模型参数值。并与一般的最短距离算法进行对比分析,结果表明,改进后的的最短距离算法所提取的转换规则在模拟城市发展时具有更高的精度,并且具有清晰的物理意义。更多还原

【Abstract】 A new method was presented to retrieve transition rules of cellular automata(CA) using an improved minimum-distance method.The core of CA is how to define transition rules in a consistent way.In most situations,transition rules of CA are defined by using heuristic methods which may be subject to some uncertainties. For example,the multicriteria evaluation(MCE) may be used to determine the parameters of transition rules.However,this method can be influenced by expert preferences.The proposed model is to define transition rules by using an improved minimum-distance method,in which the weights are determined by entropy.This method has been applied to the simulation of a fast growing city,Dongguan,in the Pearl River Delta.Comparison indicates that this method can produce better simulation accuracies than the general minimum-distance method.It model structure is transparent and can be easily understood by users.更多还原