{"title":"Spatial distribution estimation by considering the cross-correlation between components with indirect data using Gaussian process regression","authors":"Yuto Tsuda , Ikumasa Yoshida , Shinichi Nishimura","doi":"10.1016/j.sandf.2025.101624","DOIUrl":null,"url":null,"abstract":"<div><div>Generally, soil properties are measured only at limited locations. To rationally estimate the spatial distribution of soil properties, it is preferable to effectively use all available measurement data, including indirect data. We propose a Gaussian process regression with multiple random fields that considers the cross-correlation between one of the random fields of direct data and indirect data, and show the application to simulated data and actual measured data. In the application, the direct data are of CPT tip resistance (<em>qc</em>), which was obtained within a narrow area, and the indirect data are of shear wave velocity (<em>Vs</em>) obtained by surface wave exploration, which were obtained over a wide area. We estimate the spatial distribution of <em>qc</em> from the limited <em>qc</em> and wide area <em>Vs</em> data. The estimation accuracy of the proposed method is evaluated by cross-validation, and its effectiveness is discussed.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"65 3","pages":"Article 101624"},"PeriodicalIF":3.3000,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soils and Foundations","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0038080625000587","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, GEOLOGICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Generally, soil properties are measured only at limited locations. To rationally estimate the spatial distribution of soil properties, it is preferable to effectively use all available measurement data, including indirect data. We propose a Gaussian process regression with multiple random fields that considers the cross-correlation between one of the random fields of direct data and indirect data, and show the application to simulated data and actual measured data. In the application, the direct data are of CPT tip resistance (qc), which was obtained within a narrow area, and the indirect data are of shear wave velocity (Vs) obtained by surface wave exploration, which were obtained over a wide area. We estimate the spatial distribution of qc from the limited qc and wide area Vs data. The estimation accuracy of the proposed method is evaluated by cross-validation, and its effectiveness is discussed.
期刊介绍:
Soils and Foundations is one of the leading journals in the field of soil mechanics and geotechnical engineering. It is the official journal of the Japanese Geotechnical Society (JGS)., The journal publishes a variety of original research paper, technical reports, technical notes, as well as the state-of-the-art reports upon invitation by the Editor, in the fields of soil and rock mechanics, geotechnical engineering, and environmental geotechnics. Since the publication of Volume 1, No.1 issue in June 1960, Soils and Foundations will celebrate the 60th anniversary in the year of 2020.
Soils and Foundations welcomes theoretical as well as practical work associated with the aforementioned field(s). Case studies that describe the original and interdisciplinary work applicable to geotechnical engineering are particularly encouraged. Discussions to each of the published articles are also welcomed in order to provide an avenue in which opinions of peers may be fed back or exchanged. In providing latest expertise on a specific topic, one issue out of six per year on average was allocated to include selected papers from the International Symposia which were held in Japan as well as overseas.