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治安警情是反映社会整体治安状况的一个重要变量,但由于治安警情具有较强的随机性和波动性等特点,给人们进行警情的研判和预测带来了极大的困难。本文通过引入灰色模型并建立基于序列绝对误差的马尔可夫转移概率矩阵,对廊坊市2013年1-6月间的侵财类周警情时间序列进行了短期的分析和预测。结果表明:灰色-马尔可夫模型能够在灰色模型预测的基础上提高预测精度,证明灰色-马尔可夫模型在治安警情预测中具有较好的价值。
Public security and police intelligence is an important variable that reflects the overall law and order situation in society. However, due to the strong randomness and volatility of public security and police intelligence, it has brought great difficulties to the people in conducting trial and forecast of police intelligence. In this paper, by introducing the gray model and establishing the Markov transition probability matrix based on the absolute error of the sequence, a short-term analysis and prediction is made on the time series of the fortune-telling weekly intelligence in January-June 2013 in Langfang. The results show that the gray-Markov model can improve the prediction accuracy based on the gray model prediction, and prove that the gray-Markov model has good value in the security alarm prediction.