【摘要】：從時(shí)空統(tǒng)計(jì)的角度,將時(shí)空級(jí)聯(lián)模式的頻繁度評(píng)價(jià)建模為多元獨(dú)立分布零假設(shè)下的顯著性判別問(wèn)題,提出一種基于點(diǎn)過(guò)程模擬的時(shí)空級(jí)聯(lián)模式統(tǒng)計(jì)挖掘方法。首先,采用時(shí)空點(diǎn)過(guò)程模擬每類地理要素的觀測(cè)數(shù)據(jù)集,構(gòu)建顯著性判別的零模型;其次,通過(guò)蒙特卡洛模擬獲取零假設(shè)下每種候選時(shí)空級(jí)聯(lián)模式頻繁度的實(shí)驗(yàn)分布;最后,對(duì)候選模式的觀測(cè)頻繁度進(jìn)行顯著性檢驗(yàn),識(shí)別顯著的時(shí)空級(jí)聯(lián)模式。研究結(jié)果表明:本文方法能夠用于有效識(shí)別地理要素間的時(shí)空級(jí)聯(lián)模式,且避免了挖掘結(jié)果對(duì)頻繁度閾值設(shè)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(xué)地球科學(xué)與信息物理學(xué)院;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(41471385) 湖南省自然科學(xué)杰出青年基金資助項(xiàng)目(14JJ1007)~~
【分類號(hào)】：P208

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1 裴韜;李婷;周成虎;;時(shí)空點(diǎn)過(guò)程:一種新的地學(xué)數(shù)據(jù)模型、分析方法和觀察視角[J];地球信息科學(xué)學(xué)報(bào);2013年06期

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本文編號(hào)：2128919