摘要道路交通安全关乎人民的生活质量，并且也是国民经济的重要组成部分。道路交通事故是道路交通安全的主要影响因素，因此要做好道路交通安全工作，首先就应该解决道路交通事故问题。在国内外对交通事故预测的大环境下，逐步建立起了系统的研究方法，为决策者提供了有效的意见和建议。本文运用灰色预测模型与马尔可夫模型对道路交通事故死亡人数做预测。论文的主要研究内容和方法如下：86407

(1) 论文针对当下道路交通存在的安全隐患和突发事故这一突出问题，通过对交通安全现状和交通事故特点的了解，查阅并学习广大中外学者的研究成果，从而对灰色系统预测在道路交通事故这一实际问题的应用方面建立一个初步的理论体系，运用灰色模型中的GM(1，1)模型及马尔可夫模型建立预测模型，有效利用道路交通事故历史信息对未来的发展趋势进行预测，并检验其预测的精确性。

（2）论文中用到了灰色GM(1，1)模型，建模过程中涉及模型精度检验，包括残差分析、后验差比值、小概率误差等检验标准，模型建立后对原始序列进行预测，再利用改进的马尔可夫模型对数据进行修正，其中应用了滑动转移概率矩阵，对数据进行再次的预测。

毕业论文关键词：交通安全；交通事故预测；灰色预测模型；马尔可夫模型；滑动转移概率矩阵

Abstract Road traffic safety is an important part closely links to the quality of life of people, and also the national economy。 Road accidents are the main effect factors of road traffic    safety, therefore, we should do the work better about safety of road traffic。 At first, we should solve the problem of road traffic accidents。 Accidents prediction has a good environment at home and abroad, and gradually establishes a systematic research methods, it provides decision makers with effective ideas and suggestions。 This paper uses gray forecasting model and Markov model to make predictions of road traffic fatalities。 The main contents and methods are as follows:

(1)This article aim at the present outstanding problems in road traffic accidents and the hidden danger of traffic safety, through understanding the present situation of traffic safety and the characteristics of traffic accidents, review and study the broad masses research results of Chinese and foreign scholars, by the grey system prediction in the actual problem of road traffic accident applications to establish a preliminary theoretical system , use gray model GM (1,1) model and Markov model to establish the prediction model, by road traffic accident history information to predict the trends in the future , and test their predictions accuracy。

(2) This article include gray GM (1,1) model, and involves testing the accuracy of the model in the process of modeling, including the residual analysis, the difference between the ratio of posterior, small probability of error and other testing standards, the original sequence is going to be forecasted after model is established , then, using the improved Markov model to amend data, including the application of a sliding transition probability matrix, the data is again forecasted。

Keywords: traffic safety; accident prediction; gray prediction model; Markov model; slide transition probability matrix

目录

摘要 VI

Abstract VII

第一章绪论 1

1。1研究背景 1

1。1。1道路交通安全现状 1

1。1。2国内外研究现状及对应的研究方法 1

1。2论文的主要内容、研究方法