本文選題：犯罪情報(bào) + 統(tǒng)計(jì)算法��； 參考：《武漢大學(xué)》2009年博士論文

【摘要】：自上個(gè)世紀(jì)80年代以來,隨著計(jì)算機(jī)技術(shù)的不斷發(fā)展,針對(duì)不同領(lǐng)域的犯罪情報(bào)分析算法和模型層出不窮。特別是在國外,針對(duì)犯罪的行為特性、心理特性、地域特性等開展了大量有價(jià)值的定量研究,其研究成果已經(jīng)廣泛的應(yīng)用于實(shí)際工作。但是在國內(nèi),由于各種原因針對(duì)犯罪分析的定性研究遠(yuǎn)遠(yuǎn)多于定量研究；同時(shí),針對(duì)社會(huì)治安綜合狀態(tài)的犯罪分析仍屬空白領(lǐng)域；而如何有效的針對(duì)犯罪情報(bào)進(jìn)行科學(xué)分析,找出其變化內(nèi)蘊(yùn)含的信息,準(zhǔn)確分析和把握社會(huì)治安形勢(shì)變化趨勢(shì),是公安機(jī)關(guān)各項(xiàng)工作順利開展、保持社會(huì)穩(wěn)定有序的重要基礎(chǔ)。在公安部科研項(xiàng)目：“基于數(shù)據(jù)倉庫的警情預(yù)測(cè)分析系統(tǒng)”(項(xiàng)目編號(hào)：2005hbstyycx115)和“警務(wù)信息綜合平臺(tái)和警用GIS的數(shù)據(jù)交換模型研究”(項(xiàng)目編號(hào)：2007hbstyycx065)的資助下,本論文圍繞城市犯罪情報(bào)信息分析模型和算法開展了深入研究。本論文主要做了如下工作： 1.針對(duì)社會(huì)現(xiàn)實(shí)中社會(huì)治安形勢(shì)的“規(guī)律性波動(dòng)”和“警示性波動(dòng)”現(xiàn)象,在客觀分析犯罪情報(bào)研究領(lǐng)域相關(guān)成果基礎(chǔ)上,指出了犯罪情報(bào)分析在趨勢(shì)分析預(yù)警領(lǐng)域的薄弱之處,探討了在研究犯罪情報(bào)分析中使用基于統(tǒng)計(jì)的入侵檢測(cè)思想的可行性,指出了需要重點(diǎn)解決的幾個(gè)方面問題。 2.提出了基于指數(shù)衰減的城市犯罪分布特征向量,用于描述社會(huì)治安綜合狀態(tài)。該向量由若干重疊時(shí)間窗內(nèi)分布特征按一定算法衰減、疊加后用以刻畫城市社會(huì)治安綜合態(tài)勢(shì)。由于多次考慮了歷史因素的影響,該向量能較好的反應(yīng)城市犯罪統(tǒng)計(jì)特征的時(shí)間變化特性,既能表示當(dāng)前統(tǒng)計(jì)數(shù)據(jù)的特性,又能夠蘊(yùn)含歷史數(shù)據(jù)特性和現(xiàn)實(shí)表征。由于采用遞推的方法進(jìn)行構(gòu)造,該向量使用較為方便。提出了基于卡方檢驗(yàn)的原始數(shù)據(jù)預(yù)處理算法(Chi-square testing based Distribution Classifying Algorithm, CDCA),該算法通過對(duì)各類犯罪數(shù)據(jù)進(jìn)行分類、合并和剔除,獲取對(duì)犯罪數(shù)據(jù)進(jìn)行Poisson逼近的最優(yōu)區(qū)間。 3.提出了基于復(fù)合統(tǒng)計(jì)特征向量的假設(shè)檢驗(yàn)算法(Composite Statistic Profiling-Vector Hypothesis-test Algorithm, CSPHA)。CSPHA算法設(shè)計(jì)了分別體現(xiàn)數(shù)據(jù)收集、數(shù)據(jù)提取和融合、數(shù)據(jù)分析時(shí)間特征的三種時(shí)長,在不同的時(shí)間范圍內(nèi)收集業(yè)務(wù)系統(tǒng)中的分離數(shù)據(jù)、提取其統(tǒng)計(jì)特征值并構(gòu)造檢驗(yàn)向量；設(shè)計(jì)了有效的系統(tǒng)異常檢驗(yàn)式和參照異常檢驗(yàn)式以對(duì)當(dāng)前統(tǒng)計(jì)量進(jìn)行檢驗(yàn)。實(shí)驗(yàn)系統(tǒng)和實(shí)驗(yàn)室檢測(cè)結(jié)果驗(yàn)證了CSPHA算法對(duì)常態(tài)城市社會(huì)治安綜合態(tài)勢(shì)的準(zhǔn)確把握。 4.提出了蘊(yùn)含統(tǒng)計(jì)分量關(guān)聯(lián)關(guān)系的ECSPHA算法(Enhanced Composite StatisticProfiling-Vector Hypothesis-test Algorithm)。ECSPHA算法選取替代協(xié)方差矩陣以放大反應(yīng)不同類型犯罪形式之間關(guān)聯(lián)特性,優(yōu)化了檢驗(yàn)量以提高對(duì)復(fù)雜系統(tǒng)中不同參量關(guān)聯(lián)的敏感性。實(shí)驗(yàn)結(jié)果表明ECSPHA對(duì)單一統(tǒng)計(jì)數(shù)據(jù)不敏感,對(duì)關(guān)聯(lián)統(tǒng)計(jì)數(shù)據(jù)較敏感,較好的實(shí)現(xiàn)了對(duì)特殊條件下的社會(huì)治安狀態(tài)把握。 5.提出了一個(gè)基于歷史分布數(shù)據(jù)的犯罪情報(bào)分析算法(Long-term Historical Profile based Information Processing Algorithm, LHPIPA)。該算法分析各個(gè)統(tǒng)計(jì)特征量在較長歷史環(huán)境中的分布特性,通過一個(gè)標(biāo)準(zhǔn)正態(tài)分布隨機(jī)變量將不同特征量測(cè)量值進(jìn)行歸一化。算法充分考慮實(shí)際工作中具有豐富經(jīng)驗(yàn)的專家意見,在計(jì)算異常指標(biāo)時(shí)引入了人工的決策干預(yù)。實(shí)驗(yàn)結(jié)果表明了LHPIPA相對(duì)CSPHA有較好的人工科學(xué)決策和時(shí)空拓展特性。
[Abstract]:Since the last century since 80s, with the continuous development of computer technology, according to the different areas of the criminal intelligence analysis algorithms and models emerge in an endless stream. Especially in foreign countries, the behavior of crime, psychological characteristics, regional characteristics and carry out a quantitative and a lot of valuable research, its research results have been widely used in practical work. But in China, due to various reasons for the qualitative study of crime analysis is far more than the quantitative research; at the same time, according to the comprehensive analysis of the social security status crime is still a blank field; and how to effectively carry out scientific analysis for criminal information, to find out the change in the information contained, accurately analyze and grasp the changing trend of the social security situation, public security organization of the work carried out smoothly, the important foundation to maintain the stability and order of the society. In the research project of the Ministry of Public Security: "pre warning based on data warehouse Measurement and analysis system "(project number: 2005hbstyycx115) and" research model of police information integrated platform and police GIS data exchange "(project number: 2007hbstyycx065), this paper focuses on City criminal information analysis model and algorithm to carry out in-depth research. This paper mainly do the following work:
1. according to the law of social reality in the social security situation of "volatility" and "warning wave" phenomenon in the research field of objective analysis of criminal intelligence related on the basis of the results of the analysis of criminal intelligence analysis pointed out that the weakness of early warning in the field of trend, discussed in the study of crime in the information analysis the feasibility of using statistical intrusion detection theory based on the pointed out several problems need to be solved.
2. the city crime distribution feature vector based on exponential attenuation is used to describe the comprehensive social order. The state vector is composed of several overlapping time window distribution algorithm according to certain attenuation, superimposed to characterize the comprehensive situation of the city social security. Because of the multiple influence factors of history, time variation characteristics of the vector can reflect the city crime the statistical characteristics of good, not only can represent the characteristics of the current statistical data, but also contains the history and the characteristic of the data representation of reality. By using recursive method to construct the vector more convenient to use. The chi square test of the original data preprocessing algorithm based on (Chi-square testing based Distribution Classifying Algorithm, CDCA), the the algorithm through the classification of various types of crime data, merger and acquisition was removed, optimal Poisson approximation of crime data.
3. proposed composite statistical hypothesis testing algorithm based on feature vector (Composite Statistic Profiling-Vector Hypothesis-test Algorithm, CSPHA.CSPHA) algorithm is designed which reflects the data collection, data extraction and data fusion, time characteristic analysis of three kinds of long, isolated data service system in different time range, extract the statistical characteristic value and construct the test vector; design of effective system of inspection and inspection according to abnormal abnormal type of the current statistics to test. Test results verify the laboratory experimental system and CSPHA algorithm to accurately grasp the situation of social security in normal city.
4. proposed ECSPHA algorithm contains statistical correlation component (Enhanced Composite StatisticProfiling-Vector Hypothesis-test Algorithm.ECSPHA) algorithm to select alternative covariance matrix to magnify the correlation characteristics between the reactions of different forms of crime, to optimize the test in order to improve the sensitivity of different parameters related in complex systems. The experimental results show that the ECSPHA of single statistical data is not sensitive, sensitive the related statistical data, to achieve a better grasp of the special conditions of social security.
5. propose a criminal intelligence analysis algorithm based on historical data distribution (Long-term Historical Profile based Information Processing Algorithm, LHPIPA). The algorithm of distribution analysis of characteristics of all the statistics in the long historical environment, normalized by a standard normal distribution of random variables with different characteristics of measurement values. The algorithm takes full account of the expert opinions have rich experience in the practical work, making artificial intervention applied in calculation of abnormal indicators. The experimental results show that the LHPIPA CSPHA had better artificial decision-making and development of time and space characteristics.

【學(xué)位授予單位】：武漢大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2009
【分類號(hào)】：D917

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