交通事故案例检索优化方法

Case Retrieval Optimization Method for Traffic Accidents

摘要:

为提高交通事故条件下实时决策管理的准确性，提出交通事故案例检索优化方法.基于交通事故案例数值型和枚举型数据构成特征，采用信息熵方法评价数据离散程度，客观确定交通事故案例属性权重，在数据归类化处理的基础上，应用二阶聚类算法建立案例检索库，开发交通事故案例检索系统并进行案例检索试验，从案例最高相似度及案例集匹配度两方面评价案例检索精度，验证了该案例检索优化方法的有效性.

Abstract:

An optimization method for traffic accident case retrieval is proposed to improve the accuracy of real time decision management under traffic accident conditions. Based on traffic accident data constitution of Numeric and enumeration type, attribute weights are determined objectively through information entropy method evaluating the data dispersion degree. On the basis of data classification, case retrieval base is established through second order clustering algorithm. And a traffic accident case retrieval system is developed to have a series of tests. Then, case retrieval tests are conducted to verify effectiveness of this optimization method by analyzing both highest similarity and case set matching degree of the retrieval conclusions.