This invention discloses a local
transmission network evaluation method based on AI large-
scale model empowerment and hierarchical aggregation
algorithm, belonging to the field of communication network evaluation technology. The invention includes: constructing a three-level evaluation
index system; collecting
raw data from multi-source systems and performing intelligent cleaning using a weighted KNN
algorithm and dynamic box plots; mapping data according to index type using corresponding functions; integrating subjective weights from AHP and objective weights from
entropy weight method, and determining combined weights through a deviation maximization model; calculating the comprehensive capability index of the
transmission network by a bottom-up, layer-by-layer aggregation based on the combined weights; and presenting the results visually through
radar charts and combining
random forest and SHAP analysis for intelligent diagnosis. This invention solves the problems of existing evaluation systems being single-dimensional, static, lacking intelligence, and having poor
interpretability, achieving scientific quantification, dynamic evaluation, and intelligent diagnosis of multi-dimensional capabilities of transmission networks, and is applicable to network
health assessment, precise investment, and optimization decision-making.