{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:27:56Z","timestamp":1740202076615,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"abstract":"<jats:p>This paper presents a multi-parameterized water quality prediction method with differential computing among sampling sites at Bangkok City, Thailand. Here, two canals were selected for case study and nine parameters were chosen for water quality prediction, they are Temperature, pH, DO, BOD, COD, NH3-N, NO2-N, NO3-N, and TP. The data obtained from 2007 to November 2017. The differential computing is chosen to predict the parameters along sampling sites. The results are indicated the predictive values of temperature and pH are entirely accurate than another parameter because the error values are low values and both parameters are slightly changed from the past up to present. Therefore, the differential computing possibly uses to predict some water quality parameters which they are quite stable conditions.<\/jats:p>","DOI":"10.3233\/978-1-61499-933-1-195","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:27:05Z","timestamp":1740133625000},"source":"Crossref","is-referenced-by-count":0,"title":["A Multi-Parameterized Water Quality Prediction Method with Differential Computing Among Sampling Sites"],"prefix":"10.3233","author":[{"family":"Ladsavong Khoumkham","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Chawakitchareon Petchporn","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Kiyoki Yasushi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Information Modelling and Knowledge Bases XXX"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:30:58Z","timestamp":1740137458000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-932-4&spage=195&doi=10.3233\/978-1-61499-933-1-195"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-933-1-195","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2019]]}}}