【摘要】：傳統(tǒng)掃描統(tǒng)計方法在進(jìn)行時空異常聚類模式挖掘時,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)則形狀時空異常聚類模式挖掘方法stAntScan。新方法基于26方位時空鄰近單元格構(gòu)建時空鄰接矩陣,再對蟻群最優(yōu)化掃描統(tǒng)計方法進(jìn)行改進(jìn),使其能適應(yīng)三維大數(shù)據(jù)量的時空區(qū)域掃描。模擬數(shù)據(jù)和真實微博簽到數(shù)據(jù)的實驗證明,stAntScan能有效地識別時空范圍內(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】：TP311.13

【參考文獻(xiàn)】

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