Traffic accident data quality enhancement method based on generative adversarial network
The invention discloses a traffic accident data quality enhancement method based on a generative adversarial network, and the method comprises the steps: S2, carrying out the preprocessing of a traffic accident data set, and obtaining a preprocessed data set; s3, performing data filling on the prepr...
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| creator | ZHANG SHENGRUI ZHANG YING ZHOU BEI LI JIALU YU YANG |
| description | The invention discloses a traffic accident data quality enhancement method based on a generative adversarial network, and the method comprises the steps: S2, carrying out the preprocessing of a traffic accident data set, and obtaining a preprocessed data set; s3, performing data filling on the preprocessed data set by using a generative interpolation network to obtain a filled data set; s4, judging whether the filled data set meets a preset filling effect or not, and if yes, entering S5; otherwise, returning to S3; s5, performing data balancing processing on data with unbalanced categories in the filled data set to obtain a data set after data balancing processing; and S6, judging whether the data balance processing result achieves a balance effect or not, if so, outputting the data balance processing result as a quality enhancement result of the traffic accident data, and if not, taking the balance processing result as a filled data set and returning to S5. According to the invention, the loss phenomenon of |
| format | Patent |
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According to the invention, the loss phenomenon of</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS ; SIGNALLING ; TRAFFIC CONTROL SYSTEMS</subject><creationdate>2023</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=20230905&DB=EPODOC&CC=CN&NR=116701853A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230905&DB=EPODOC&CC=CN&NR=116701853A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>ZHANG SHENGRUI</creatorcontrib><creatorcontrib>ZHANG YING</creatorcontrib><creatorcontrib>ZHOU BEI</creatorcontrib><creatorcontrib>LI JIALU</creatorcontrib><creatorcontrib>YU YANG</creatorcontrib><title>Traffic accident data quality enhancement method based on generative adversarial network</title><description>The invention discloses a traffic accident data quality enhancement method based on a generative adversarial network, and the method comprises the steps: S2, carrying out the preprocessing of a traffic accident data set, and obtaining a preprocessed data set; s3, performing data filling on the preprocessed data set by using a generative interpolation network to obtain a filled data set; s4, judging whether the filled data set meets a preset filling effect or not, and if yes, entering S5; otherwise, returning to S3; s5, performing data balancing processing on data with unbalanced categories in the filled data set to obtain a data set after data balancing processing; and S6, judging whether the data balance processing result achieves a balance effect or not, if so, outputting the data balance processing result as a quality enhancement result of the traffic accident data, and if not, taking the balance processing result as a filled data set and returning to S5. According to the invention, the loss phenomenon of</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</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>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNizsOwjAQBd1QIOAOywGQsCI-LYpAVFQp6KKHvSEWjh3sJYjbAxIHoJpiZsbqXCU0jTMEY5zlIGQhoPsD3smLOLQIhruv6FjaaOmCzJZioCsHThA3MMEOnDKSg6fA8ozpNlWjBj7z7MeJmh_2VXlccB9rzj3MZ5e6PGm93iz1dlXsin-aN8x6OsE</recordid><startdate>20230905</startdate><enddate>20230905</enddate><creator>ZHANG SHENGRUI</creator><creator>ZHANG YING</creator><creator>ZHOU BEI</creator><creator>LI JIALU</creator><creator>YU YANG</creator><scope>EVB</scope></search><sort><creationdate>20230905</creationdate><title>Traffic accident data quality enhancement method based on generative adversarial network</title><author>ZHANG SHENGRUI ; ZHANG YING ; ZHOU BEI ; LI JIALU ; YU YANG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116701853A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</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>ZHANG SHENGRUI</creatorcontrib><creatorcontrib>ZHANG YING</creatorcontrib><creatorcontrib>ZHOU BEI</creatorcontrib><creatorcontrib>LI JIALU</creatorcontrib><creatorcontrib>YU YANG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>ZHANG SHENGRUI</au><au>ZHANG YING</au><au>ZHOU BEI</au><au>LI JIALU</au><au>YU YANG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Traffic accident data quality enhancement method based on generative adversarial network</title><date>2023-09-05</date><risdate>2023</risdate><abstract>The invention discloses a traffic accident data quality enhancement method based on a generative adversarial network, and the method comprises the steps: S2, carrying out the preprocessing of a traffic accident data set, and obtaining a preprocessed data set; s3, performing data filling on the preprocessed data set by using a generative interpolation network to obtain a filled data set; s4, judging whether the filled data set meets a preset filling effect or not, and if yes, entering S5; otherwise, returning to S3; s5, performing data balancing processing on data with unbalanced categories in the filled data set to obtain a data set after data balancing processing; and S6, judging whether the data balance processing result achieves a balance effect or not, if so, outputting the data balance processing result as a quality enhancement result of the traffic accident data, and if not, taking the balance processing result as a filled data set and returning to S5. According to the invention, the loss phenomenon of</abstract><oa>free_for_read</oa></addata></record> |
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| language | chi ; eng |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS SIGNALLING TRAFFIC CONTROL SYSTEMS |
| title | Traffic accident data quality enhancement method based on generative adversarial network |
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