Network Link Health Assessment Method Based on Cloud Model and Vikor

The health assessment of train network links lacks quantitative analysis, and expert evaluation opinions often conflict, making it difficult to meet the high requirements for train network link security in the new era. To address this issue, this article proposes a network link health assessment method based on cloud models and VIKOR methods to address the problems of fuzziness, randomness, and multi-criteria conflicts in link health assessment in complex train network environments. This method designs a multi-expert scoring mechanism, uses the golden ratio method to convert language evaluation scales into cloud model digital features, dynamically assigns expert weights based on cloud similarity, and aggregates them to form a cloud decision matrix. Innovatively combining the subjective experience of the Analytic Hierarchy Process and the objective analysis of the Cloud Entropy Weight Method to determine the comprehensive weights, and ultimately constructing the Cloud VIKOR evaluation framework. This method can effectively handle the ambiguity of parameters such as latency and packet loss rate, and achieve optimal compromise ranking under conflict indicators. Very suitable for link health assessment in highly complex train systems.