【摘要】：從時空統(tǒng)計的角度,將時空級聯模式的頻繁度評價建模為多元獨立分布零假設下的顯著性判別問題,提出一種基于點過程模擬的時空級聯模式統(tǒng)計挖掘方法。首先,采用時空點過程模擬每類地理要素的觀測數據集,構建顯著性判別的零模型;其次,通過蒙特卡洛模擬獲取零假設下每種候選時空級聯模式頻繁度的實驗分布;最后,對候選模式的觀測頻繁度進行顯著性檢驗,識別顯著的時空級聯模式。研究結果表明:本文方法能夠用于有效識別地理要素間的時空級聯模式,且避免了挖掘結果對頻繁度閾值設置的依賴。
[Abstract]:From the point of view of space-time statistics, the frequency evaluation of spatio-temporal cascaded patterns is modeled as a significant discrimination problem under the assumption of zero multivariate independent distribution, and a statistical mining method of spatio-temporal cascaded patterns based on point process simulation is proposed. Firstly, the spatio-temporal point process is used to simulate the observational data set of each kind of geographical elements, and the zero model of significant discrimination is constructed. Secondly, the experimental distribution of the frequency of each candidate spatio-temporal cascade model under zero assumption is obtained by Monte Carlo simulation. The observational frequency of candidate models was tested to identify significant spatio-temporal cascade patterns. The results show that the proposed method can be used to identify spatio-temporal cascade patterns between geographical elements effectively and avoid the dependence of mining results on frequency threshold setting.
【作者單位】： 中南大學地球科學與信息物理學院;
【基金】：國家自然科學基金資助項目(41471385) 湖南省自然科學杰出青年基金資助項目(14JJ1007)~~
【分類號】：P208

【相似文獻】

相關期刊論文 前1條

1 裴韜;李婷;周成虎;;時空點過程:一種新的地學數據模型、分析方法和觀察視角[J];地球信息科學學報;2013年06期

，

本文編號：2128919