Factors Affecting Evaluation of Railway Bulk Freight Rate: A Novel Cloud Theory-Based Approach

Abstract

Railway freight rates are seen as a key driving factor of global trade activities, influenced by numerous factors. Given the limitations of fuzziness and randomness of variable quantification in the previous studies, this paper proposes a cognitive cloud model of factors influencing railway bulk goods freight rates. In the cognitive cloud model, randomness and fuzziness are described by three parameters. Furthermore, a cloud generator including forwarding and backward cloud generators is designed to solve the bidirectional conversion between qualitative indicators and quantitative values. In addition, we propose a floating cloud gathering algorithm to determine the weight of the index system to solve the uncertainty problem in the transformation process of qualitative indicators. Finally, the cognitive cloud model and the adapted algorithm are used to perform an in-depth analysis of the affecting factors of Z Railway Bureau freight transport pricing.