Application of Data Analysis in Trend Prediction of Different Crime Types in London

• 作者: Chenguang Zhang Dianting Liu Jingwen Tang
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: DATA PREDICTION ARIMA MODEL DATA analysis
• 年，卷（期）: 2019,（2）
• 页码范围: 465-467
• 页数: 3页
• 分类号: C

摘要

This paper aims to analyze the data of different crime types in the London area for the past three years. The data is from data.police.uk provided by City of London Police. The R language and ARIMA model were applied to forecast different crime types in London. Seven sets of stable non-white sequences were obtained by preprocessing the original data, stationary test, and non-stationary sequence differential processing. The time series analysis method was used to realize the ARIMA model modelling. After comparison, the prediction was performed with the optimal ARIMA model. In terms of anti-social behaviour (i1), public order (i9), robbery (i10), shoplifting (i11), theft from the person (i12), the predicted results show a small fluctuation. And it shows a large fluctuation trend in bicycle theft (i2), but the overall number is lower than the previous months. Violence and sexual offences (i14) show a downtrend.