{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T17:54:08Z","timestamp":1770141248252,"version":"3.49.0"},"reference-count":37,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of Shandong Province","award":["ZR2022ME214"],"award-info":[{"award-number":["ZR2022ME214"]}]},{"name":"Natural Science Foundation of Shandong Province","award":["BHKF2022Z03"],"award-info":[{"award-number":["BHKF2022Z03"]}]},{"name":"Open Fund of the Key Laboratory of Geological Safety of Coastal Urban Underground Space, Ministry of Natural Resources","award":["ZR2022ME214"],"award-info":[{"award-number":["ZR2022ME214"]}]},{"name":"Open Fund of the Key Laboratory of Geological Safety of Coastal Urban Underground Space, Ministry of Natural Resources","award":["BHKF2022Z03"],"award-info":[{"award-number":["BHKF2022Z03"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>The accurate prediction of urban road collapses is of paramount importance for public safety and infrastructure management. However, the complex and variable nature of road subsidence mechanisms, coupled with the inherent noise and non-stationarity in the data, poses significant challenges to the development of precise and real-time prediction models. To address these challenges, this paper develops an Adaptive Difference Least Squares Support Vector Regression (AD-LSSVR) model. The AD-LSSVR model employs a difference transformation to process the input and output data, effectively reducing noise and enhancing model stability. This transformation extracts trends and features from the data, leveraging the symmetrical characteristics inherent within it. Additionally, the model parameters were optimized using grid search and cross-validation techniques, which systematically explore the parameter space and evaluate model performance of multiple subsets of data, ensuring both precision and generalizability of the selected parameters. Moreover, a sliding window method was employed to address data sparsity and anomalies, ensuring the robustness and adaptability of the model. The experimental results demonstrate the superior adaptability and precision of the AD-LSSVR model in predicting road collapse timing, highlighting its effectiveness in handling the complex nonlinear data.<\/jats:p>","DOI":"10.3390\/sym16080977","type":"journal-article","created":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T15:26:53Z","timestamp":1722526013000},"page":"977","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Adaptive Difference Least Squares Support Vector Regression for Urban Road Collapse Timing Prediction"],"prefix":"10.3390","volume":"16","author":[{"given":"Yafang","family":"Han","sequence":"first","affiliation":[{"name":"Key Laboratory of Geological Safety of Coastal Urban Underground Space, Ministry of Natural Resources, Qingdao 266061, China"},{"name":"Qingdao Key Laboratory of Groundwater Resources Protection and Rehabilitation, Qingdao 266061, China"},{"name":"Qingdao Geo-Engineering Surveying Institute (Qingdao Geological Exploration Development Bureau), Qingdao 266061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Limin","family":"Quan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geological Safety of Coastal Urban Underground Space, Ministry of Natural Resources, Qingdao 266061, China"},{"name":"Qingdao Key Laboratory of Groundwater Resources Protection and Rehabilitation, Qingdao 266061, China"},{"name":"School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanchun","family":"Liu","sequence":"additional","affiliation":[{"name":"Qingdao Geo-Engineering Surveying Institute (Qingdao Geological Exploration Development Bureau), Qingdao 266061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minghou","family":"Li","sequence":"additional","affiliation":[{"name":"Qingdao Geo-Engineering Surveying Institute (Qingdao Geological Exploration Development Bureau), Qingdao 266061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Shan","sequence":"additional","affiliation":[{"name":"Qingdao Geo-Engineering Surveying Institute (Qingdao Geological Exploration Development Bureau), Qingdao 266061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,1]]},"reference":[{"key":"ref_1","first-page":"134","article-title":"The impact of urbanization on underground infrastructure: A systematic review","volume":"15","author":"Smith","year":"2022","journal-title":"Urban Infrastruct. 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