本文選題：基于Agent建模與仿真　切入點：傳染病監(jiān)測　出處：《系統(tǒng)仿真學報》2017年09期

【摘要】：空間聚類廣泛用于傳染病的監(jiān)測、預防和控制。傳染病與普通疾病在早期具有相似的癥狀,使得傳染病數(shù)據(jù)處理和分析更為困難。采用基于Agent的仿真建模方法,生成北京暴發(fā)H1N1流感的仿真數(shù)據(jù)�；�4組分布形狀與規(guī)模不同的數(shù)據(jù),對2種空間聚類算法的疫情監(jiān)測結果進行分析。結果表明,通過空間聚類算法對Agent仿真數(shù)據(jù)進行分析,有助于揭示疫情的擴散規(guī)律,進而在傳染病監(jiān)測和防控方面起到積極作用。
[Abstract]:Spatial clustering is widely used in surveillance, prevention and control of infectious diseases. Infectious diseases and common diseases have similar symptoms in the early stage, which makes data processing and analysis of infectious diseases more difficult. The simulation data of Beijing H1N1 influenza outbreak were generated. Based on four groups of data with different distribution shapes and scales, the epidemic monitoring results of two spatial clustering algorithms were analyzed. The results showed that the Agent simulation data were analyzed by spatial clustering algorithm. It is helpful to reveal the law of epidemic spread and play an active role in infectious disease surveillance and prevention and control.
【作者單位】： 國防科技大學信息系統(tǒng)與管理學院;中國空間技術研究院通信衛(wèi)星事業(yè)部;
【基金】：國家自然科學基金(71373282)
【分類號】：R511.7;TP391.9
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本文編號：1690292