Abstract
The article considers the proprietary method of ranking the territory of the railway influence, based on the use of vulnerability matrices and application of cluster analysis, which allows optimizing the decision-making process for responding to emergencies associated with rail transport. The "point" ranking of vulnerabilities in the zone of railway influence was used for more accurate information on the events with applying the identity matrices of vulnerabilities. The partition cell is taken as a single "point". The method is based on the ranking of ecological, economic, environmental, bioresource and cultural significance of the territory by means of defining identical matrices of vulnerabilities that describe each point of the event. The partition cells were grouped into three clusters: moderately vulnerable territory, highly vulnerable territory and extremely vulnerable territory. The result of using the method was the compiling of vulnerability ranking maps.
Highlights
The issues of ensuring security in railway transport are among the top-priority issues in the development of Russian transport sector
"Strategy for the Development of Russian Railways up to 2030" [1] implies the elabortion of measures aimed at improving the security system on railway transport
The authors of the present article developed a method for ranking the railway influence territory using vulnerability matrices and applying the cluster analysis
Summary
The issues of ensuring security in railway transport are among the top-priority issues in the development of Russian transport sector. The issues of zoning the railway in terms of emergency risk are considered in the works [2, 3, 4]. In this context, the authors of the present article developed a method for ranking the railway influence territory using vulnerability matrices and applying the cluster analysis. The authors of the present article developed a method for ranking the railway influence territory using vulnerability matrices and applying the cluster analysis This method enables optimizing the decision-making taking into account the rational disposing of emergency response facilities associated with rail transportation
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