I. Spassiani, S. Gentili, R. Console, M. Murru, M. Taroni, G. Falcone
{"title":"调和不可调和的矛盾:基于窗口的算法与随机去聚类算法","authors":"I. Spassiani, S. Gentili, R. Console, M. Murru, M. Taroni, G. Falcone","doi":"arxiv-2408.16491","DOIUrl":null,"url":null,"abstract":"Short-term earthquake clustering is one of the most important features of\nseismicity. Clusters are identified using various techniques, generally\ndeterministic and based on spatio-temporal windowing. Conversely, the leading\nrail in short-term earthquake forecasting has a probabilistic view of\nclustering, usually based on the Epidemic Type Aftershock Sequence (ETAS)\nmodels. In this study we compare seismic clusters, identified by two different\ndeterministic window-based techniques, with the ETAS probabilities associated\nwith any event in the clusters, thus investigating the consistency between\ndeterministic and probabilistic approaches. The comparison is performed by\nconsidering, for each event in an identified cluster, the corresponding\nprobability of being independent and the expected number of triggered events\naccording to ETAS. Results show no substantial differences between the cluster\nidentification procedures, and an overall consistency between the identified\nclusters and the relative events' ETAS probabilities.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"2 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reconciling the irreconcilable: window-based versus stochastic declustering algorithms\",\"authors\":\"I. Spassiani, S. Gentili, R. Console, M. Murru, M. Taroni, G. Falcone\",\"doi\":\"arxiv-2408.16491\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Short-term earthquake clustering is one of the most important features of\\nseismicity. Clusters are identified using various techniques, generally\\ndeterministic and based on spatio-temporal windowing. Conversely, the leading\\nrail in short-term earthquake forecasting has a probabilistic view of\\nclustering, usually based on the Epidemic Type Aftershock Sequence (ETAS)\\nmodels. In this study we compare seismic clusters, identified by two different\\ndeterministic window-based techniques, with the ETAS probabilities associated\\nwith any event in the clusters, thus investigating the consistency between\\ndeterministic and probabilistic approaches. The comparison is performed by\\nconsidering, for each event in an identified cluster, the corresponding\\nprobability of being independent and the expected number of triggered events\\naccording to ETAS. Results show no substantial differences between the cluster\\nidentification procedures, and an overall consistency between the identified\\nclusters and the relative events' ETAS probabilities.\",\"PeriodicalId\":501270,\"journal\":{\"name\":\"arXiv - PHYS - Geophysics\",\"volume\":\"2 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - PHYS - Geophysics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2408.16491\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Geophysics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.16491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reconciling the irreconcilable: window-based versus stochastic declustering algorithms
Short-term earthquake clustering is one of the most important features of
seismicity. Clusters are identified using various techniques, generally
deterministic and based on spatio-temporal windowing. Conversely, the leading
rail in short-term earthquake forecasting has a probabilistic view of
clustering, usually based on the Epidemic Type Aftershock Sequence (ETAS)
models. In this study we compare seismic clusters, identified by two different
deterministic window-based techniques, with the ETAS probabilities associated
with any event in the clusters, thus investigating the consistency between
deterministic and probabilistic approaches. The comparison is performed by
considering, for each event in an identified cluster, the corresponding
probability of being independent and the expected number of triggered events
according to ETAS. Results show no substantial differences between the cluster
identification procedures, and an overall consistency between the identified
clusters and the relative events' ETAS probabilities.