A comprehensive bridge efficiency evaluation system comprising 30 indicators across five levels was intro-duced.Indicator weights were derived using the G1 method and reliability theory.A substantial sample database with 7 100entries was generated via the cubic spline interpolation method.To optimize the Extreme Learning Machines(ELM)performance,the Dung Beetle Optimization(DBO)algorithm was employed,yielding an evaluation model with an average error margin below 2％.An efficiency analysis of a 65-meter steel-composite small box girder bridge yielded an overall ef-ficiency score of 92.34.Detailed scores include:93.37 for safety,95.05 for applicability,92.4 for durability,90.04 for pro-tection,and 88.83 for green economy.These findings illustrate the high comprehensive efficiency of this bridge type,con-sidering investment cost,construction duration,and environmental impact.The proposed methodology and results provide a robust framework for informed investment,design,and construction decisions in bridge engineering.
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