City anomaly detection method and device based on probability distribution
The invention discloses a probability distribution-based city anomaly detection method and device. The method comprises the following steps of: dividing a city region according to city road network data to obtain city sub-regions; vehicle track data are obtained through preprocessing; according to t...
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| creator | NIU XINZHENG GUO JINGJING LIU HONG TANG BO XIE QILIN NIE YANBIN MA YONG YE LIBIN |
| description | The invention discloses a probability distribution-based city anomaly detection method and device. The method comprises the following steps of: dividing a city region according to city road network data to obtain city sub-regions; vehicle track data are obtained through preprocessing; according to the vehicle trajectory data, time period traffic inflow and time period traffic outflow of the urban sub-regions in historical 30 days are counted, and then an inflow probability distribution set and an outflow probability distribution set of the urban sub-regions are constructed by using an FPD method; detecting and marking anomalies in the incoming flow probability distribution set and the outgoing flow probability distribution set by using an LOF algorithm; obtaining a current detection database of the to-be-detected city sub-region by finding out the approximate region; according to the current detection database, using an LOF algorithm to determine whether there is an abnormal event in the to-be-detected city s |
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The method comprises the following steps of: dividing a city region according to city road network data to obtain city sub-regions; vehicle track data are obtained through preprocessing; according to the vehicle trajectory data, time period traffic inflow and time period traffic outflow of the urban sub-regions in historical 30 days are counted, and then an inflow probability distribution set and an outflow probability distribution set of the urban sub-regions are constructed by using an FPD method; detecting and marking anomalies in the incoming flow probability distribution set and the outgoing flow probability distribution set by using an LOF algorithm; obtaining a current detection database of the to-be-detected city sub-region by finding out the approximate region; according to the current detection database, using an LOF algorithm to determine whether there is an abnormal event in the to-be-detected city s</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS ; SIGNALLING ; TRAFFIC CONTROL SYSTEMS</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240514&DB=EPODOC&CC=CN&NR=118038688A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25543,76294</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240514&DB=EPODOC&CC=CN&NR=118038688A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>NIU XINZHENG</creatorcontrib><creatorcontrib>GUO JINGJING</creatorcontrib><creatorcontrib>LIU HONG</creatorcontrib><creatorcontrib>TANG BO</creatorcontrib><creatorcontrib>XIE QILIN</creatorcontrib><creatorcontrib>NIE YANBIN</creatorcontrib><creatorcontrib>MA YONG</creatorcontrib><creatorcontrib>YE LIBIN</creatorcontrib><title>City anomaly detection method and device based on probability distribution</title><description>The invention discloses a probability distribution-based city anomaly detection method and device. The method comprises the following steps of: dividing a city region according to city road network data to obtain city sub-regions; vehicle track data are obtained through preprocessing; according to the vehicle trajectory data, time period traffic inflow and time period traffic outflow of the urban sub-regions in historical 30 days are counted, and then an inflow probability distribution set and an outflow probability distribution set of the urban sub-regions are constructed by using an FPD method; detecting and marking anomalies in the incoming flow probability distribution set and the outgoing flow probability distribution set by using an LOF algorithm; obtaining a current detection database of the to-be-detected city sub-region by finding out the approximate region; according to the current detection database, using an LOF algorithm to determine whether there is an abnormal event in the to-be-detected city s</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><subject>SIGNALLING</subject><subject>TRAFFIC CONTROL SYSTEMS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZPByziypVEjMy89NzKlUSEktSU0uyczPU8hNLcnITwFKpAAFyzKTUxWSEotTUxSAUgVF-UmJSZk5II0pmcUlRZlJpSA9PAysaYk5xam8UJqbQdHNNcTZQze1ID8-tbggMTk1L7Uk3tnP0NDCwNjCzMLC0ZgYNQA4uzVx</recordid><startdate>20240514</startdate><enddate>20240514</enddate><creator>NIU XINZHENG</creator><creator>GUO JINGJING</creator><creator>LIU HONG</creator><creator>TANG BO</creator><creator>XIE QILIN</creator><creator>NIE YANBIN</creator><creator>MA YONG</creator><creator>YE LIBIN</creator><scope>EVB</scope></search><sort><creationdate>20240514</creationdate><title>City anomaly detection method and device based on probability distribution</title><author>NIU XINZHENG ; GUO JINGJING ; LIU HONG ; TANG BO ; XIE QILIN ; NIE YANBIN ; MA YONG ; YE LIBIN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN118038688A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><topic>SIGNALLING</topic><topic>TRAFFIC CONTROL SYSTEMS</topic><toplevel>online_resources</toplevel><creatorcontrib>NIU XINZHENG</creatorcontrib><creatorcontrib>GUO JINGJING</creatorcontrib><creatorcontrib>LIU HONG</creatorcontrib><creatorcontrib>TANG BO</creatorcontrib><creatorcontrib>XIE QILIN</creatorcontrib><creatorcontrib>NIE YANBIN</creatorcontrib><creatorcontrib>MA YONG</creatorcontrib><creatorcontrib>YE LIBIN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>NIU XINZHENG</au><au>GUO JINGJING</au><au>LIU HONG</au><au>TANG BO</au><au>XIE QILIN</au><au>NIE YANBIN</au><au>MA YONG</au><au>YE LIBIN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>City anomaly detection method and device based on probability distribution</title><date>2024-05-14</date><risdate>2024</risdate><abstract>The invention discloses a probability distribution-based city anomaly detection method and device. The method comprises the following steps of: dividing a city region according to city road network data to obtain city sub-regions; vehicle track data are obtained through preprocessing; according to the vehicle trajectory data, time period traffic inflow and time period traffic outflow of the urban sub-regions in historical 30 days are counted, and then an inflow probability distribution set and an outflow probability distribution set of the urban sub-regions are constructed by using an FPD method; detecting and marking anomalies in the incoming flow probability distribution set and the outgoing flow probability distribution set by using an LOF algorithm; obtaining a current detection database of the to-be-detected city sub-region by finding out the approximate region; according to the current detection database, using an LOF algorithm to determine whether there is an abnormal event in the to-be-detected city s</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS SIGNALLING TRAFFIC CONTROL SYSTEMS |
| title | City anomaly detection method and device based on probability distribution |
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