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FOREST PEST OCCURRENCE PREDICTION USING CA-MARKOV MODEL

机译:基于CA-MARKOV模型的森林害虫发生率预测

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Since the spatial pattern of forest pest occurrence is determined by biologicalcharacteristics and habitat conditions, this paper introduced construction of a cellular automaton model combined with Markov model to predicate the forest pest occurrence. Rules of the model includes the cell states rules, neighborhood rules and transition rules which are defined according to the factors from stand conditions, stand structures, climate and the influence of the factors on the state conversion. Coding for the model is also part of the implementations of the model. The participants were designed including attributes and operations of participants expressed with a UML diagram. Finally, the scale issues on forest pest occurrence prediction, of which the core are the prediction of element size and time interval, are partly discussed in this paper.
机译:由于森林有害生物发生的空间格局是由生物学决定的 的特点和生境条件,本文介绍了结合马尔可夫模型的元胞自动机模型的构建,以预测森林病虫害的发生。模型的规则包括单元状态规则,邻域规则和过渡规则,它们是根据林分条件,林分结构,气候以及这些因素对状态转换的影响而定义的。该模型的编码也是该模型的实现的一部分。参与者的设计包括使用UML图表示的参与者的属性和操作。最后,本文对森林有害生物发生预测的尺度问题进行了部分讨论,其中以元素大小和时间间隔的预测为核心。

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