{"title":"Multi-input integrative neural network for soil seismic response modeling at KiK-net downhole array sites","authors":"Lin Li, Feng Jin, Duruo Huang, Gang Wang","doi":"10.1002/eqe.4155","DOIUrl":null,"url":null,"abstract":"<p>Prediction of the soil seismic response is of primary importance for geotechnical earthquake engineering. Conventional physics-based models such as the finite element method (FEM) often face challenges due to inherent model assumptions and uncertainties of model parameters. Furthermore, these physics-based models require significant computational resources, particularly when simulating seismic responses across numerous soil sites. In this study, a multi- input integrative neural network is developed for predicting soil seismic response based on the recorded data from a large number of downhole array sites. Ground motions, seismic event information, and wave velocity structures of the sites are utilized as input data in the proposed neural network, enabling the model to adapt to various site conditions. Comparative assessments against state-of-the-art FEM models demonstrate that the proposed models exhibit superior prediction performance with increased efficiency. Furthermore, the pre-training technique, a transfer learning method, is employed to predict the seismic response at new stations. By fine-tuning the pre-trained model derived from the extensive dataset with limited recorded data from new stations, high-precision seismic response predictions can be realized, illustrating the adaptability and efficacy of the proposed approach in data-scarce conditions.</p>","PeriodicalId":11390,"journal":{"name":"Earthquake Engineering & Structural Dynamics","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earthquake Engineering & Structural Dynamics","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/eqe.4155","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
Prediction of the soil seismic response is of primary importance for geotechnical earthquake engineering. Conventional physics-based models such as the finite element method (FEM) often face challenges due to inherent model assumptions and uncertainties of model parameters. Furthermore, these physics-based models require significant computational resources, particularly when simulating seismic responses across numerous soil sites. In this study, a multi- input integrative neural network is developed for predicting soil seismic response based on the recorded data from a large number of downhole array sites. Ground motions, seismic event information, and wave velocity structures of the sites are utilized as input data in the proposed neural network, enabling the model to adapt to various site conditions. Comparative assessments against state-of-the-art FEM models demonstrate that the proposed models exhibit superior prediction performance with increased efficiency. Furthermore, the pre-training technique, a transfer learning method, is employed to predict the seismic response at new stations. By fine-tuning the pre-trained model derived from the extensive dataset with limited recorded data from new stations, high-precision seismic response predictions can be realized, illustrating the adaptability and efficacy of the proposed approach in data-scarce conditions.
期刊介绍:
Earthquake Engineering and Structural Dynamics provides a forum for the publication of papers on several aspects of engineering related to earthquakes. The problems in this field, and their solutions, are international in character and require knowledge of several traditional disciplines; the Journal will reflect this. Papers that may be relevant but do not emphasize earthquake engineering and related structural dynamics are not suitable for the Journal. Relevant topics include the following:
ground motions for analysis and design
geotechnical earthquake engineering
probabilistic and deterministic methods of dynamic analysis
experimental behaviour of structures
seismic protective systems
system identification
risk assessment
seismic code requirements
methods for earthquake-resistant design and retrofit of structures.