基于改进熵值法的隧道照明环境评价研究

doi:10.3969/j.issn.1674-0696.2023.07.15

重庆交通大学学报（自然科学版） ›› 2023, Vol. 42 ›› Issue (7): 113-119.DOI: 10.3969/j.issn.1674-0696.2023.07.15

• 交通基础设施工程 • 上一篇

基于改进熵值法的隧道照明环境评价研究

闫自海1，李硕2，甘鹏路1，梁思农1

(1. 中国电建集团华东勘察设计研究院有限公司，浙江杭州 311122； 2. 重庆交通大学土木工程学院，重庆 400074)

收稿日期:2021-03-02 修回日期:2021-08-19 发布日期:2023-09-08
作者简介:闫自海（1984—），男，浙江杭州人，高级工程师，主要从事城市隧道设计方面的工作。E-mail：85383258@qq.com 通信作者：李硕（1996—），男，山东济南人，硕士研究生，主要从事隧道及地下工程安全运营方面的研究。E-mail：1154300467@qq.com
基金资助:
国家自然科学基金项目（51878107）；华东勘测设计研究院项目（KY2019-JT-25）

Tunnel Lighting Environment Evaluation Based on Improved Entropy Method

YAN Zihai1, LI Shuo2, GAN Penglu1, LIANG Sinong1

(1. Power China Huadong Engineering Corporation Limited, Hangzhou 311122, Zhejiang, China; 2. College of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China)

Received:2021-03-02 Revised:2021-08-19 Published:2023-09-08

摘要/Abstract

摘要： 针对现有隧道照明环境评价方法主观性较强、考虑评价指标单一的问题，从光源、交通状况、通风条件以及空间通视性4个方面选取评价指标，利用改进熵值法明确各评价指标的影响程度，并结合基于BP神经网络的模型简化和基于聚类分析的安全等级划分，构建隧道照明环境评价体系。研究结果表明：权重计算结果充分反映了实测数据本身蕴涵的信息，解决了由于数据离散程度较大导致指标权重值较大的问题；基于BP神经网络的照明环境评价简化模型计算精度较高，计算拟合判断系数R2=0.934；经检验瞳孔面积变化率均值、中位数均与评估值的变化规律基本保持一致，评估值W可以有效评估隧道内部照明环境综合危险程度。

关键词: 隧道工程；照明环境；安全评价；改进熵值法；权重

Abstract: Aiming at the problems of strong subjectivity and single evaluation index in the existing tunnel lighting environment evaluation methods, the evaluation indicators were selected from four aspects: light source, traffic conditions, ventilation conditions and spatial visibility. The improved entropy method was used to clarify the impact degree of each evaluation indicator, and combining the model simplification based on BP neural network and the safety level classification based on clustering analysis, a tunnel lighting environment evaluation system was constructed. The research results show that the weight calculation results fully reflect the information contained in the measured data itself and solve the problem of the large index weight value due to the large degree of data dispersion. The simplified model for lighting environment evaluation based on BP neural network has high calculation accuracy, and the fitting judgment coefficient R2=0.934 is calculated. After inspection, the mean and median changes in pupil area are basically consistent with the variation pattern of the evaluation value. The evaluation value W can effectively evaluate the comprehensive risk level of the tunnel interior lighting environment.

Key words: tunnel engineering; lighting environment; safety evaluation; improved entropy method; weight

中图分类号:

U458.1

闫自海1，李硕2，甘鹏路1，梁思农1. 基于改进熵值法的隧道照明环境评价研究[J]. 重庆交通大学学报（自然科学版）, 2023, 42(7): 113-119.

YAN Zihai1, LI Shuo2, GAN Penglu1, LIANG Sinong1. Tunnel Lighting Environment Evaluation Based on Improved Entropy Method[J]. Journal of Chongqing Jiaotong University(Natural Science), 2023, 42(7): 113-119.

参考文献

［1］ MA Z Y, FANG S E, LIU S, et al. Analysis of the relationship between the number of traffic accidents and the traffic flow & section location in extra-long tunnel［J］. Engineering, 2020, 12(2): 71-81.
［2］杜志刚，梅家林，倪玉丹,等.基于视觉需求的城市水下特长隧道光环境评价与优化综述［J］.交通运输工程学报,2020,20(6):48-61.
DU Zhigang, MEI Jialin, NI Yudan, et al. Review on evaluation and optimization of light environment of extra-long urban underwater tunnel based on visual demands ［J］. Journal of Traffic and Transportation Engineering, 2020, 20(6): 48-61.
［3］李志勇, 朱尚书. 明色化铺装材料的路用性能研究［J］. 重庆交通大学学报（自然科学版）, 2023, 42(2): 37-43.
LI Zhiyong, ZHU Shangshu. Roadperformance of light-colored pavement materials［J］. Journal of Chongqing Jiaotong University(Natural Science), 2023, 42(2): 37-43.
［4］ LU J, XING Y, WANG C, et al. Risk factors affecting the severity of traffic accidents at shanghai river-crossing tunnel［J］. Traffic Injury Prevention, 2016, 17(2): 176-180.
［5］戴忧华，郭忠印，马艳，等．高速公路隧道运行环境安全评价指标［J］.同济大学学报(自然科学版),2010,38(8):1171-1176.
DAI Youhua,GUO Zhongyin, MA Yan, et al. Safety evaluation index of driving environment of expressway tunnel［J］. Journal of Tongji University (Natural Science), 2010, 38(8): 1171-1176.
［6］ MA Yingqi, LU Linjun, LU Jian John. Safety evaluation model of urban cross-river tunnel based on driving simulation［J］. International Journal of Injury Control and Safety Promotion, 2017, 24(3):293-302.
［7］何世永,梁波,钟升明,等.基于光环境室内仿真和视觉功效实验的公路隧道照明评价方法研究［J］.重庆交通大学学报(自然科学版),2020,39(03):27-35.
HE Shiyong, LIANG Bo, ZHONG Shengming,et al. Evaluation method of highway tunnel lighting based on indoor simulation of light environ-ment and visual performance experiment［J］. Journal of Chongqing Jiaotong University(Natural Science), 2020, 39(3): 27-35.
［8］何坚，张成龙，张凡，等．基于虚拟现实的隧道交通设施与环境评估技术［J］.同济大学学报(自然科学版),2020,48(2):215-222.
HE Jian, ZHANG Chenglong, ZHANG Fan,et al. Tunnel traffic facili-ties and environment assessment technology based on virtual reality［J］. Journal of Tongji University (Natural Science Edition), 2020, 48(2): 215-222.
［9］戴忧华, 郭忠印. 空间通视性对高速公路隧道路段驾驶行为的影响［J］. 同济大学学报(自然科学版), 2011, 39(9):1307-1312.
DI Youhua, GUO Zhongyin. Effect of spatial visual pattern on driving behavior in expressway tunnel section［J］. Journal of Tongji University (Natural Science Edition), 2011, 39(9): 1307-1312.
［10］黄国庆，王明绪，王国良．效能评估中的改进熵值法赋权研究［J］.计算机工程与应用,2012,48(28):245-248.
HUANG Guoqing, WANG Mingxu, WANG Guoliang.Weight assign-ment research of improved entropy method in effectiveness evaluation ［J］. Computer Engineering and Applications,2012, 48(28):245-248.
［11］赵兴东，牛佳安，汪为平，等．基于BP神经网络的矿石非计划贫化预测［J］.金属矿山,2021(7):34-39.
ZHAO Xingdong, NIU Jiaan, WANG Weiping,et al. Prediction of unplan-ned dilution of ore based on BP neural network［J］. Metal Mine, 2021(7): 34-39.
［12］ XIAO Qiang, HE Ruichun, YU Jianning. Evaluation of taxi carpooling feasibility in different urban areas through the K-means matter-element analysis method［J］.Technology in Society, 2018, 53: 135-143.
［13］ HE Shiyong, LIANG Bo, PAN Guobing, et al. Influence of dynamic high-way tunnel lighting environment on driving safety based on eye movement parameters of the driver［J］. Tunnelling and Underground Space Technology, 2017, 67:52-60.

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基于改进熵值法的隧道照明环境评价研究

Tunnel Lighting Environment Evaluation Based on Improved Entropy Method

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