Traffic Noise Prediction

Suman Mann, Gyanendra Singh
{"title":"Traffic Noise Prediction","authors":"Suman Mann, Gyanendra Singh","doi":"10.57159/gadl.jcmm.2.6.230104","DOIUrl":null,"url":null,"abstract":"Traffic noise prediction models are crucial for designing highways to implement preventive measures against traffic noise pollution by analyzing future trends. This study aims to identify the traffic, road geometrical, and environmental parameters that escalate traffic noise pollution, enabling rectification of influencing factors and enhancement of strategies to reduce this pollution. A traffic noise prediction model was developed for the highways of Delhi-NCR using the Multiple Regression approach, incorporating various traffic, geometric, and environmental parameters. Statistical analysis was conducted, and the model was formulated based on data collected from 31 sampling stations on two major Delhi highways. Significant variables identified include the number of lanes, average building height, international roughness index, temperature, wind speed, and humidity. The model’s validity is affirmed by a coefficient of determination R2 = 0.75, indicating a good fit.","PeriodicalId":372188,"journal":{"name":"Journal of Computers, Mechanical and Management","volume":"23 24","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computers, Mechanical and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.57159/gadl.jcmm.2.6.230104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Traffic noise prediction models are crucial for designing highways to implement preventive measures against traffic noise pollution by analyzing future trends. This study aims to identify the traffic, road geometrical, and environmental parameters that escalate traffic noise pollution, enabling rectification of influencing factors and enhancement of strategies to reduce this pollution. A traffic noise prediction model was developed for the highways of Delhi-NCR using the Multiple Regression approach, incorporating various traffic, geometric, and environmental parameters. Statistical analysis was conducted, and the model was formulated based on data collected from 31 sampling stations on two major Delhi highways. Significant variables identified include the number of lanes, average building height, international roughness index, temperature, wind speed, and humidity. The model’s validity is affirmed by a coefficient of determination R2 = 0.75, indicating a good fit.
交通噪音预测
交通噪声预测模型对于设计高速公路,通过分析未来趋势来实施交通噪声污染预防措施至关重要。本研究旨在确定导致交通噪声污染加剧的交通、道路几何和环境参数,从而纠正影响因素并加强减少污染的策略。采用多元回归方法,结合各种交通、几何和环境参数,为德里--中北部地区的高速公路开发了一个交通噪声预测模型。根据从德里两条主要高速公路的 31 个采样站收集到的数据进行了统计分析,并制定了模型。确定的重要变量包括车道数、建筑物平均高度、国际粗糙度指数、温度、风速和湿度。模型的确定系数 R2 = 0.75 表明拟合效果良好,从而证实了模型的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信