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公安工作疫情流調(diào)大數(shù)據(jù)建模和安全分析
網(wǎng)絡(luò)安全與數(shù)據(jù)治理 4期
田學(xué)成1,韓 寧2
(1.國電南京自動(dòng)化股份有限公司,江蘇 南京211100;2.武威市公安局涼州分局,甘肅 武威733000)
摘要: 根據(jù)疫情流調(diào)數(shù)據(jù)特點(diǎn),建立流調(diào)數(shù)據(jù)模型量化防疫具體需求。為了快速篩選出防疫需求的數(shù)據(jù),基于MySQL數(shù)據(jù)庫使用多條件數(shù)據(jù)查詢及過濾、數(shù)據(jù)分組、數(shù)據(jù)清洗方法,并使用Python第三方庫Pandas對(duì)流調(diào)數(shù)據(jù)做時(shí)間間隔計(jì)算。最后,在此基礎(chǔ)上對(duì)模型數(shù)據(jù)做可視化處理,直觀地反映流調(diào)數(shù)據(jù)情況,并對(duì)流調(diào)數(shù)據(jù)的傳輸作了安全分析。本文數(shù)據(jù)處理方法對(duì)基層民警提高大數(shù)據(jù)處理效率有借鑒意義,對(duì)疫情防疫流調(diào)工作有重要意義。
中圖分類號(hào): G203
文獻(xiàn)標(biāo)識(shí)碼: A
DOI: 10.19358/j.issn.2097-1788.2022.04.005
引用格式: 田學(xué)成,韓寧. 公安工作疫情流調(diào)大數(shù)據(jù)建模和安全分析[J].網(wǎng)絡(luò)安全與數(shù)據(jù)治理,2022,41(4):31-36.
Big data modeling and security analysis of epidemic situation investigation in public security work
Tian Xuecheng1,Han Ning2
(1.Guodian Nanjing Automation Co.,Ltd.,Nanjing 211100,China; 2.Liangzhou Branch of Wuwei Public Security Bureau,Wuwei 733000,China)
Abstract: In this paper, the original data model is established according to the epidemic flow survey data to quantify the specific needs of epidemic prevention. Based on the MySQL database, multi-condition data filtering,grouping and data cleaning methods are used, and Pandas, a third-party Python library, is used to filter the epidemiological data. The purpose is to quickly screen the data required for epidemic prevention. Finally, the model data is visually processed to intuitively reflect the epidemiological data. And the security analysis of the transmission of the flow modulation data is made.The data processing method in this paper can be used by grass-roots police to improve the efficiency of big data processing, and is of great significance to epidemic prevention and epidemic control.
Key words : epidemiological data;MySQL;Pandas;data filtering;visualization

0 引言

當(dāng)前國內(nèi)疫情形勢(shì)仍然嚴(yán)峻,防控正處于關(guān)鍵緊要時(shí)期,在“外防輸入、內(nèi)防輸出、動(dòng)態(tài)清零”的總體要求下,開展精準(zhǔn)流調(diào)工作至關(guān)重要。疫情期間開展流調(diào)工作需要依托大數(shù)據(jù)支持,數(shù)據(jù)處理結(jié)果關(guān)乎疫情防疫政策的實(shí)施,如何對(duì)流調(diào)數(shù)據(jù)快速精準(zhǔn)的定位和篩選是地方政府疫情防疫環(huán)節(jié)中重要的一環(huán)。而目前流調(diào)數(shù)據(jù)普遍呈現(xiàn)出零碎化、非結(jié)構(gòu)化特點(diǎn),導(dǎo)致公安民警在進(jìn)行流調(diào)數(shù)據(jù)處理工作時(shí),需要投入了大量時(shí)間成本和寶貴人力。本文基于MySQL數(shù)據(jù)庫快速篩選出符合條件的數(shù)據(jù),將大數(shù)據(jù)處理變得自動(dòng)化、靈活化,提高疫情流調(diào)工作的效率,提高民警對(duì)大數(shù)據(jù)處理的工作效率,為防疫工作爭取更多時(shí)間,更好地將精力投入后期的安全防控措施中去,同時(shí)減輕基層公安民警工作負(fù)擔(dān)。本文對(duì)疫情流調(diào)數(shù)據(jù)處理方法適用于臨時(shí)情況下數(shù)據(jù)處理任務(wù)。基于流調(diào)數(shù)據(jù)特點(diǎn),建立流調(diào)數(shù)據(jù)模型。圖1是流調(diào)數(shù)據(jù)處理流程。





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作者信息:

田學(xué)成1,韓  寧2

(1.國電南京自動(dòng)化股份有限公司,江蘇 南京211100;2.武威市公安局涼州分局,甘肅 武威733000)


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