研究表明，不同的地貌要素具有不同的概率分布模式；
The theoretic distributions of the geomorphic factors are selected.
考虑不属于该领域的文本特征，可以有效地增加不同类文本特征模式之间的距离并优化其概率分布。
Considering all fields of text features can increase the distance between text feature pattern of each other and optimize their probability distribution.
该方法通过对时间序列排序模式进行分类，来实现复杂的概率分布估计，从而直接估计出时间序列的信息量。
The proposed method calculates the probability distribution of time series based on the classification of order patterns to directly estimate the amount of information in time series.
针对模式分类中高置信度的先验概率分布难以设定的问题，提出了一种新的应用贝叶斯分析进行模式分类的方法。
To overcome the hardship of enacting the pre-probability distribution with high certainty factor, this paper proposes one novel way of applying Bayes analysis to classify pattern.
③确定典型活动模式的概率分布。
Thirdly, estimating the representative patterns'choice probability distribution;
运用产生降水的指标性物理量分布、卫星云图降水概率分布和模式的降水预报等综合确定作业区的地理位置。
The operation location can be determined by means of precipitation indexes, precipitation probability of satellite cloud pictures and model forecasts.
运用产生降水的指标性物理量分布、卫星云图降水概率分布和模式的降水预报等综合确定作业区的地理位置。
The operation location can be determined by means of precipitation indexes, precipitation probability of satellite cloud pictures and model forecasts.
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