国际数学建模大赛一等奖论文-Research on the Location and Time of Serial Criminals.doc

For office use only T1 ________________ T2 ________________ T3 ________________ T4 ________________ Team Control Number ? Problem ChosenB For office use only F1 ________________ F2 ________________ F3 ________________ F4 ________________ Research on the Location and Time of Serial Criminals February 22,2010 Abstract Twisted souls and antisocial spirits have resulted in serial murders. In order to prevent such crimes which cause great harm to public security, the paper has established effective early warning systems and efficient detection programs by using mathematical models so that we can reduce the number of potential victims significantly. Warning preparations: First, the paper makes a statistical analysis of the victims’ personality characterictics (such as physical characteristics, clothing, occupations, etc.), locations and time of the criminal offenses, then the paper has a Principal Factor Analysis of those factors so that we can rule out the obvious or non-intrinsic factors. The principal factors obtained above are the characteristics of the crime targets in the serial murders. According to the conclusion, early warnings are given to the vulnerable groups and residents with the same situation, residence and daily schedule so as to strengthen their vigilance. Scheme One: The Establishment of Geographical Profile Based on Time-Series Analysis Model According to the statistics of the locations of serial crimes, the paper predicts the distance between adjacent cases via GPS (Global Positioning System) and establishes a time series analysis model. The paper uses SPSS software to predict the distance between the possible locations of the next crime and the past crime scenes. The data of the serial murders committed by Peter Sutcliffe and of the serial robberies in Dallas are used to verify the model: at 95% confidence level, the data obtained tally with the real circumstances. Scheme Two: The Establishment of Geographical Profile Based on the Adaptive Ne