{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1362544419906519680.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.1785/0120130208"}},{"identifier":{"@type":"URI","@value":"https://syndication.highwire.org/content/doi/10.1785/0120130208"}}],"dc:title":[{"@value":"Bayesian Approach for Identification of Multiple Events in an Early Warning System"}],"description":[{"notation":[{"@value":"The 2011 Tohoku earthquake (M_w 9.0) was followed by a large number of aftershocks that resulted in 70 early warning messages in the first month after the mainshock. Of these warnings, a non‐negligible fraction (63%) were false warnings in which the largest expected seismic intensities were overestimated by at least two intensities or larger. These errors can be largely attributed to multiple concurrent aftershocks from distant origins that occur within a short period of time. Based on a Bayesian formulation that considers the possibility of having more than one event present at any given time, we propose a novel likelihood function suitable for classifying multiple concurrent earthquakes, which uses amplitude information. We use a sequential Monte Carlo heuristic whose complexity grows linearly with the number of events. We further provide a particle filter implementation and empirically verify its performance with the aftershock records after the Tohoku earthquake. The initial case studies suggest promising performance of this method in classifying multiple seismic events that occur closely in time."}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1380567007855995649","@type":"Researcher","foaf:name":[{"@value":"A. Liu"}]},{"@id":"https://cir.nii.ac.jp/crid/1382544419906519681","@type":"Researcher","foaf:name":[{"@value":"M. Yamada"}]}],"publication":{"publicationIdentifier":[{"@type":"PISSN","@value":"00371106"}],"prism:publicationName":[{"@value":"Bulletin of the Seismological Society of America"}],"dc:publisher":[{"@value":"Seismological Society of America (SSA)"}],"prism:publicationDate":"2014-05-13","prism:volume":"104","prism:number":"3","prism:startingPage":"1111","prism:endingPage":"1121"},"reviewed":"false","dcterms:accessRights":"http://purl.org/coar/access_right/c_abf2","url":[{"@id":"https://syndication.highwire.org/content/doi/10.1785/0120130208"}],"createdAt":"2014-05-14","modifiedAt":"2017-11-03","foaf:topic":[{"@id":"https://cir.nii.ac.jp/all?q=500","dc:title":"500"}],"relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1050859215937057536","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Automatic hypocenter determination with the IPFx method for the 2018 Hualien earthquake sequence"}]},{"@id":"https://cir.nii.ac.jp/crid/1360565169815030016","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"The Propagation of Local Undamped Motion (PLUM) Method: A Simple and Robust Seismic Wavefield Estimation Approach for Earthquake Early Warning"}]},{"@id":"https://cir.nii.ac.jp/crid/1360588380592255744","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Performance of the earthquake early warning system for the 2024 Noto Peninsula earthquake"}]},{"@id":"https://cir.nii.ac.jp/crid/1360863415715682816","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Bayesian updating of model parameters using adaptive Gaussian process regression and particle filter"}]},{"@id":"https://cir.nii.ac.jp/crid/1390001204304598272","@type":"Article","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"en","@value":"A New Approach to Identify Multiple Concurrent Events for Improvement of Earthquake Early Warning"},{"@language":"ja","@value":"緊急地震速報のための同時多発地震を識別する震源推定手法"},{"@language":"ja-Kana","@value":"キンキュウ ジシン ソクホウ ノ タメ ノ ドウジ タハツ ジシン オ シキベツ スル シンゲン スイテイ シュホウ"}]},{"@id":"https://cir.nii.ac.jp/crid/2050588891959348992","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Earthquake early warning for the 2016 Kumamoto earthquake : performance evaluation of the current system and the next-generation methods of the Japan Meteorological Agency"}]}],"dataSourceIdentifier":[{"@type":"CROSSREF","@value":"10.1785/0120130208"},{"@type":"OPENAIRE","@value":"doi_dedup___::8d36fda8367bb2f899757aea8c8f2a23"},{"@type":"CROSSREF","@value":"10.4294/zisin.67.41_references_DOI_MAmj92Vfawb3anhYU6gOEroCghM"},{"@type":"CROSSREF","@value":"10.1016/j.strusafe.2023.102328_references_DOI_MAmj92Vfawb3anhYU6gOEroCghM"},{"@type":"CROSSREF","@value":"10.1785/0120170085_references_DOI_MAmj92Vfawb3anhYU6gOEroCghM"},{"@type":"CROSSREF","@value":"10.1007/s44195-022-00018-y_references_DOI_MAmj92Vfawb3anhYU6gOEroCghM"},{"@type":"CROSSREF","@value":"10.1186/s40623-025-02172-2_references_DOI_MAmj92Vfawb3anhYU6gOEroCghM"},{"@type":"CROSSREF","@value":"10.1186/s40623-016-0567-1_references_DOI_MAmj92Vfawb3anhYU6gOEroCghM"}]}