Herein, a safety evaluation method of mountainous
tunnel structures is established using an extreme learning machine (ELM)
improved by multi-criteria compromise solution sorting
method (VIKOR) and sparrow search algorithm (SSA). Previous researches on the
influencing factors of tunnel structure safety in mountainous areas are
analyzed to build an evaluation set, indicator system, and benchmarks for the
safety of tunnel structures in mountainous areas. Then, the analytic hierarchy process, entropy
weight method + criteria importance through intercriteria correlation method,
and game theory are employed to calculate the weights of evaluation indicators.
The VIKOR decision model is adopted to quantify the safety levels of tunnel
structures, and the constructed samples generated by MATLAB are transformed
into training samples for machine learning. Based on the parameter optimization
results, an SSA-ELM model is constructed, and 48
engineering instance samples, which had undergone field surveys and safety level
determinations, are collected for simulation prediction. Comparative analysis
is conducted with the original ELM and the particle warm optimization algorithm-optimized ELM model. The results indicate that the SSA-ELM model has higher prediction accuracy.
WANG Zhilong
,
YANG Wenbo
,
KOU Hao
,
ZHAO Liangliang
,
ZENG Zerun
,
WU Fangyin
. Safety Evaluation Method for Mountainous Tunnel
Structures Based on Multi-Criteria
Compromise Solution Sorting-Sparrow Search Algorithm-Extreme Learning Machine Model[J]. Tunnel Construction, 2025
, 45(S1)
: 136
-145
.
DOI: 10.3973/j.issn.2096-4498.2025.S1.015
