Evaluation of the Application Effectiveness of the SPTN Health Management System Based on Evidential Reasoning Method

With the widespread adoption of software-defined packet transport network (SPTN) health management systems, evaluating their application effectiveness faces challenges such as complex multi-source data fusion, strong subjectivity in indicator weight allocation, and inadequate uncertainty handling. Traditional evaluation methods struggle to meet the precision and robustness requirements for quantifying system performance. To address these issues, this paper proposes an evidence-based reasoning approach for assessing SPTN network system application effectiveness, achieving scientific quantification of system performance through multi-source evidence fusion. For weight determination, a composite weighting model is designed, integrating the Entropy Weight Method and the Fuzzy Analytic Hierarchy Process (FAHP). The Entropy Weight Method generates weights based on the objective distribution of data, while the FAHP addresses the uncertainty in expert judgments through fuzzy mathematics, combining the advantages of subjective and objective approaches to optimize weight allocation. For evidence reliability assessment, the information consistency method is introduced. By quantifying similarity and consistency among evidence sources, it dynamically adjusts reliability parameters, effectively mitigating uncertainty impacts in multi-source data fusion. This approach significantly enhances evaluation precision and reliability through a systematic evidential reasoning framework. It provides scientific theoretical support and methodological guidance for SPTN network system performance optimization, demonstrating strong versatility and practical value. The methodology is generalizable to evaluation scenarios in other complex network systems.