数据挖掘技术在内河交通事故分析和预防中的应用

Analysis and Prevention of Inland Waterway Casualty (IWC) by Data Mining

近年来内河船舶交通事故,特别是重特大恶性交通事故的接连发生,给人民的生命和财产安全带来了巨大的威胁。由于内河交通事故系统的高度复杂性,传统的分析预防方法已呈现其局限性。为克服事故数据库中数据多维、稀疏、不全等的不利影响,有效地识别和发现事故数据的新模式及其内在规律,提出我们应用数据挖掘技术全面整理、分析内河船舶交通事故的思想,并结合数据挖掘实现的方法和应用实例进行具体阐述,以期为船舶安全管理提供科学的决策依据。

Traditional approaches are incompetent due to complexity of the system of Inland Waterway Casualty (IWC) for the IWC analysis and prevention. In order to identify and find new modes and inherent laws of casualty data effectively from a multi-dimensional sparse and defective IWC database, this paper presents an idea of applying data mining technique to investigate casualties, and discusses some models as well as real cases of application. It is expected that data mining will aid the scientific decision-making for management of navigation safety.