道路交通事故灰色预测模型及应用研究

Grey Prediction Model for Road Traffic Accident and Its Application Research

道路交通系统是一个动态的不确定性系统,交通事故的发生具有随机性。针对道路交通系统“部分信息已知,部分信息未知”的特征,采用灰色系统理论,着重研究“小样本、贫信息”的不确定问题及“外延明确、内涵不明确”的随机对象,实现“少数据建模”。本文通过灰色生成算子的作用弱化随机性,挖掘潜在规律,经过灰色差分方程与灰色微分方程之间的互换实现了利用离散数据序列建立连续动态微分方程的过程,对交通事故进行预测及精度检验。实例分析结果表明,此方法能够更加合理、科学、准确地预测交通事故的发展态势。

Road traffic system is a dynamic uncertain system, so the occurrence of the traffic accidents has the randomicity. Aiming at the characteristic that the known, but other partial partial information of road traffic system is information is unkown, grey system theories are adopted to do mainly research on the uncertain problems of ＂small sample, poor information＂ and the stochastic objects of ＂explicit extension, inexplicit connotation＂, to build the mathematical models with a small quantity of data. The forecast model and its accuracy test for the traffic accidents are carried out in this paper by which effect of grey generator operator weakens data randomicity to excavate data＇s latent rules, and interchange of grey difference equation and grey differential equation realize the process in which continuous dynamic differential equation is built with the disperse data sequence. An application example of the method provided here demonstrates that the method can more reasonably and accurately forecast development condition of the traffic accidents.