Missing data imputation for transfer passenger flow identified from in-station WiFi systems

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dc.contributor.authorJiang, Wenhuako
dc.contributor.authorZheng, Nanko
dc.contributor.authorKim, Inhiko
dc.date.accessioned2023-02-17T05:00:09Z-
dc.date.available2023-02-17T05:00:09Z-
dc.date.created2023-01-28-
dc.date.issued2023-02-
dc.identifier.citationTRANSPORTMETRICA B-TRANSPORT DYNAMICS, v.11, no.1, pp.325 - 342-
dc.identifier.issn2168-0566-
dc.identifier.urihttp://hdl.handle.net/10203/305199-
dc.description.abstractThis paper presents a new perspective for in-station transfer flow estimation, utilising data collected by WiFi sensor system, which is critical for path choice modelling and pedestrian management. The full in-station transfer flow can be estimated by scaling up a 'seed matrix', which is constructed based on the identification of inter-platform transfer activities. Due to sensor failures, the main problem comes from handling the missing elements in the constructed 'seed matrix'. We address this problem with a novel kernel-based framework, named self-measuring multi-task Gaussian process (SM-MTGP). The heterogeneous correlations in temporal features are captured by the designed task-based and input-based kernels separately. Moreover, a self-measuring kernel is designed for learning the correlations carried by the observations. The performance of the proposed method is validated with data from a busy railway station. The results show that the proposed algorithm achieves the best imputation accuracy in both accuracy and robustness, especially at high missing rates.-
dc.languageEnglish-
dc.publisherTAYLOR & FRANCIS LTD-
dc.titleMissing data imputation for transfer passenger flow identified from in-station WiFi systems-
dc.typeArticle-
dc.identifier.wosid000791905500001-
dc.identifier.scopusid2-s2.0-85132594471-
dc.type.rimsART-
dc.citation.volume11-
dc.citation.issue1-
dc.citation.beginningpage325-
dc.citation.endingpage342-
dc.citation.publicationnameTRANSPORTMETRICA B-TRANSPORT DYNAMICS-
dc.identifier.doi10.1080/21680566.2022.2064935-
dc.contributor.localauthorKim, Inhi-
dc.contributor.nonIdAuthorJiang, Wenhua-
dc.contributor.nonIdAuthorZheng, Nan-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorWiFi data-
dc.subject.keywordAuthormissing data-
dc.subject.keywordAuthortransfer flow-
dc.subject.keywordAuthormultitask Gaussian process-
dc.subject.keywordPlusTRAFFIC FLOW-
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