{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T10:49:49Z","timestamp":1744714189795},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684444","type":"print"},{"value":"9781643684451","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,11,30]]},"abstract":"<jats:p>Aiming at the problem of water pollution classification, a water pollutant classification method based on multi-classification support vector machine is proposed. By constructing and optimizing the coding matrix, a classification coding table and decoding table are formed, and SVM sub-classifiers are used for data classification. The classification experiment was carried out on the measured water quality data of the sewage treatment plant. The results show that, compared with other traditional classification methods, this method has a higher classification accuracy rate, greatly reduces the number of sub-classifiers required, and improves the classification efficiency.<\/jats:p>","DOI":"10.3233\/faia230810","type":"book-chapter","created":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T15:53:31Z","timestamp":1701446011000},"source":"Crossref","is-referenced-by-count":1,"title":["Water Pollutant Classification Method Based on Multi-Class Support Vector Machine"],"prefix":"10.3233","author":[{"given":"Hengming","family":"Liu","sequence":"first","affiliation":[{"name":"School of Marine Technology and Environment, Dalian Ocean University, Dalian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuwen","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Environment, Hohai University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Advances in Artificial Intelligence, Big Data and Algorithms"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230810","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T15:53:33Z","timestamp":1701446013000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230810"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,30]]},"ISBN":["9781643684444","9781643684451"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230810","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,30]]}}}