Toward Prediction of Traffic Accidents Using Formal Concept Analysis of Actual Accidents and Related Data

Shogo Kotani, Masaki Nakamura, K. Sakakibara, Tatsuo Motoyoshi, Keisuke Hoshikawa
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Abstract

This study uses Formal Concept Analysis (FCA) to investigate factors of traffic accidents by analyzing actual traffic accident data including its date, place, injury severity, road shape, accident summary in a natural language, etc for each accident. FCA is a mathematical theory of data analysis based on formal contexts and concept lattices. We gather data related to each of the traffic accidents such as land use districts, traffic volumes, and so on, translate them into a binary context table as an input of FCA, and analyze conceptual structures as an output of FCA to investigate traffic accident factors.
利用实际事故及相关数据的形式概念分析预测交通事故
本研究采用形式概念分析(Formal Concept Analysis, FCA),通过分析实际的交通事故数据,包括事故发生的日期、地点、伤害严重程度、道路形状、事故的自然语言总结等,来调查交通事故的因素。FCA是一种基于形式语境和概念格的数据分析数学理论。我们收集每个交通事故的相关数据,如土地使用区域、交通量等,将其转换为二进制上下文表作为FCA的输入,并分析概念结构作为FCA的输出,以调查交通事故因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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