【摘要】：傳統(tǒng)掃描統(tǒng)計(jì)方法在進(jìn)行時(shí)空異常聚類模式挖掘時(shí),受掃描窗口形狀的限制,不能準(zhǔn)確地獲取聚類區(qū)域形狀。提出一種改進(jìn)的不規(guī)則形狀時(shí)空異常聚類模式挖掘方法stAntScan。新方法基于26方位時(shí)空鄰近單元格構(gòu)建時(shí)空鄰接矩陣,再對(duì)蟻群最優(yōu)化掃描統(tǒng)計(jì)方法進(jìn)行改進(jìn),使其能適應(yīng)三維大數(shù)據(jù)量的時(shí)空區(qū)域掃描。模擬數(shù)據(jù)和真實(shí)微博簽到數(shù)據(jù)的實(shí)驗(yàn)證明,stAntScan能有效地識(shí)別時(shí)空范圍內(nèi)的不規(guī)則形狀異常聚類,并且準(zhǔn)確性較經(jīng)典的SaTScan方法高。
[Abstract]:The traditional scanning statistical method can not accurately obtain the shape of clustering region because of the limitation of scanning window shape when mining spatio-temporal anomaly clustering pattern. An improved clustering pattern mining method for irregular shape spatio-temporal anomalies, stAntScan. is proposed. The new method is based on 26 azimuth spatio-temporal adjacent cells to construct spatio-temporal adjacency matrix, and then improves the ant colony optimization scanning statistical method to adapt to the spatio-temporal scanning of 3D large amount of data. The experimental results of simulated data and real Weibo check-in data show that stAntScan can effectively identify irregular shape anomaly clustering in space-time range, and its accuracy is higher than that of the classical SaTScan method.
【作者單位】： 武漢大學(xué)資源與環(huán)境科學(xué)學(xué)院;中國科學(xué)院亞熱帶農(nóng)業(yè)生態(tài)研究所;
【基金】：國家自然科學(xué)基金(41471327,41001231)~~
【分類號(hào)】：TP311.13

【參考文獻(xiàn)】

相關(guān)期刊論文 前3條

1 劉啟亮;鄧敏;彭東亮;王佳t，

本文編號(hào)：2122198