Abstract
This paper applied a new method based on clustering and SVD to railway emergency rescue decision-making, for it can provide an applicable, intelligent and efficient decision-making method for railway emergency rescue with high-dimensional data. The method SVD has been used to process the feature attributes of cases according to feature attribute extraction of emergency cases. Then the paper structured a railway emergency rescue decision-making model based on clustering method. Following it, a specific example was used to illustrate the railway unconventional emergency decision-making process based on clustering and SVD method, and the results showed the clustering and SVD method can meet the railway emergency decision-making requirement to a large extent. This paper made up the shortage of speculative knowledge in this aspect, offered a new method and idea in the railway emergency decision support system intelligent area which mainly depends on the individual experience.
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