乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T02:12:07Z","timestamp":1724292727015},"reference-count":59,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T00:00:00Z","timestamp":1651449600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41971355"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Transactions in GIS"],"published-print":{"date-parts":[[2022,8]]},"abstract":"Abstract<\/jats:title>Existing spatiotemporal similarity analysis methods for trajectories have the problems of spatiotemporal unsynchronization and low efficiency in processing large\u2010scale datasets, which cannot satisfy the increasingly urgent requirements of real\u2010time or quasi\u2010real\u2010time applications. To address these problems, this article proposes a grid\u2010based and synchronized spatiotemporal similarity analysis method based on the spatiotemporal grid model called gsstSIM. First, a low\u2010dimensional and multi\u2010scale trajectory coding representation is implemented based on the spatiotemporal grid model. Second, a synchronized spatiotemporal similarity measure is proposed based on trajectory codes. It transforms the similarity analysis from complex geometric calculations to simple algebraic operations of code sets, which reduces the computational complexity. In addition, the trajectory encoding representation with space\u2010time collinearity enables gsstSIM to measure the synchronized spatiotemporal similarity. Third, the efficient Multi\u2010scale grid index, called MSGrid, is established to realize fast query of top\u2010K similar trajectories for large\u2010scale datasets. Experimental results demonstrate that gsstSIM is more robust to noise positioning points and various sampling rates than the state\u2010of\u2010the\u2010art algorithms STLCSS, TWS and SWS. It can achieve a second\u2010level response of spatiotemporal similarity query in processing large\u2010scale datasets, which is much faster than existing algorithms. The proposed method has promising to support the applications with high time\u2010efficiency requirements such as epidemic tracking and traffic condition calculation.<\/jats:p>","DOI":"10.1111\/tgis.12944","type":"journal-article","created":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T09:11:14Z","timestamp":1651482674000},"page":"2206-2224","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["gsstSIM: A high\u2010performance and synchronized similarity analysis method of spatiotemporal trajectory based on grid model representation"],"prefix":"10.1111","volume":"26","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-3135-092X","authenticated-orcid":false,"given":"Jun","family":"Li","sequence":"first","affiliation":[{"name":"College of Geoscience and Surveying Engineering China University of Mining and Technology \u2010 Beijing Beijing China"}]},{"given":"Juqing","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Geoscience and Surveying Engineering China University of Mining and Technology \u2010 Beijing Beijing China"}]},{"given":"Linwei","family":"Qiao","sequence":"additional","affiliation":[{"name":"College of Geoscience and Surveying Engineering China University of Mining and Technology \u2010 Beijing Beijing China"}]},{"given":"Yaoyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Geoscience and Surveying Engineering China University of Mining and Technology \u2010 Beijing Beijing China"}]},{"given":"Wenle","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Geoscience and Surveying Engineering China University of Mining and Technology \u2010 Beijing Beijing China"}]},{"given":"Chengye","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Geoscience and Surveying Engineering China University of Mining and Technology \u2010 Beijing Beijing China"}]},{"given":"Qian","family":"Huang","sequence":"additional","affiliation":[{"name":"Service Lab Huawei Technology Co. 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