Mohammad Pourhomayoun, Mehran Mazari, Luis Fisher, Kabir Nagrecha, Tonatiuh Rodriguez-Nikl, Michael Mooney, Ehsan Alavi
{"title":"利用递归神经网络和盾构隧道掘进机数据预测地质成分","authors":"Mohammad Pourhomayoun, Mehran Mazari, Luis Fisher, Kabir Nagrecha, Tonatiuh Rodriguez-Nikl, Michael Mooney, Ehsan Alavi","doi":"10.1080/10286608.2023.2286248","DOIUrl":null,"url":null,"abstract":"Tunnel Boring Machines (TBMs) are large-scale excavation tools used commonly in transportation tunnel construction. While tunnelling, TBMs generate data at large scales, often at levels difficult t...","PeriodicalId":50689,"journal":{"name":"Civil Engineering and Environmental Systems","volume":"183 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction of geological composition using recurrent neural networks and shield tunnel boring machine data\",\"authors\":\"Mohammad Pourhomayoun, Mehran Mazari, Luis Fisher, Kabir Nagrecha, Tonatiuh Rodriguez-Nikl, Michael Mooney, Ehsan Alavi\",\"doi\":\"10.1080/10286608.2023.2286248\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tunnel Boring Machines (TBMs) are large-scale excavation tools used commonly in transportation tunnel construction. While tunnelling, TBMs generate data at large scales, often at levels difficult t...\",\"PeriodicalId\":50689,\"journal\":{\"name\":\"Civil Engineering and Environmental Systems\",\"volume\":\"183 1\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Civil Engineering and Environmental Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/10286608.2023.2286248\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Civil Engineering and Environmental Systems","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/10286608.2023.2286248","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Prediction of geological composition using recurrent neural networks and shield tunnel boring machine data
Tunnel Boring Machines (TBMs) are large-scale excavation tools used commonly in transportation tunnel construction. While tunnelling, TBMs generate data at large scales, often at levels difficult t...
期刊介绍：
Civil Engineering and Environmental Systems is devoted to the advancement of systems thinking and systems techniques throughout systems engineering, environmental engineering decision-making, and engineering management. We do this by publishing the practical applications and developments of "hard" and "soft" systems techniques and thinking.
Submissions that allow for better analysis of civil engineering and environmental systems might look at:
-Civil Engineering optimization
-Risk assessment in engineering
-Civil engineering decision analysis
-System identification in engineering
-Civil engineering numerical simulation
-Uncertainty modelling in engineering
-Qualitative modelling of complex engineering systems
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
