The Identified Method of Accident-Prone Section Based on Principal Component-Gray Clustering Analysis

• DOI: 10.4028/www.scientific.net/amm.135-136.1060
• Publication Date: 2011-10-27T12:06:22Z
• Authors: Jin Jiang Liu; Mei He; Hong Ke Xu; Qi Wang; Yong Mei Yang
• Keywords: Gray (unit); Section (typography)

In order to study the rapid and efficient identified method of accident-prone section in montane highway, principal component - gray clustering analysis has been proposed. By deep characteristics section, indexes have screened out, reducing dimensionality incomplete information processing organically integrated, weight coefficients are creatively determined based on content. Based data investigation treatment, using components analysis, security level sections is achieved by programming. The results show that this high precision convenience aspects aggregative indicators selected value calculated. can effectively identify divide into 4-grade. Aiming at results, measures further researched. So practical value.