摘要
为提出一种集市政道路结构强度模型设计、训练优化与结果验证于一体的深度学习的解决方案,本研究在数据采集基础上收集市政道路典型案例进行验证,从多角度对模型进行了全面评估及性能测试,为智能化市政道路管理提供了支持。研究结果表明:该方法在强度计算的精度、鲁棒性和计算效率方面均优于传统方法,具有工程适用性与推广价值。
In order to propose a deep learning solution that integrates municipal road structure strength model design,training optimization and result validation,based on the data acquisition,this study collects typical cases of municipal roads to validate,and comprehensively evaluates and performs performance tests on the model from multiple perspectives,to provide supports for intelligent municipal road management.The results show that this method is superior to the traditional method in strength calculation accuracy,robustness and efficiency,and has high engineering applicability and popularization value.
作者
杨久宁
YANG Jiuning(Gansu Engineering Design and Research Institute Co.,Ltd.,Lanzhou 730030,China)
出处
《科技创新与生产力》
2025年第5期123-125,共3页
Sci-tech Innovation and Productivity
关键词
深度学习
市政道路
结构强度
强度计算
性能测试
模型优化
deep learning
municipal road
structural strength
strength calculation
performance test
model optimization
