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Determination of biochemical oxygen demand and dissolved oxygen for semi-arid river environment: application of soft computing models

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dc.citedby24
dc.contributor.authorTao H.en_US
dc.contributor.authorBobaker A.M.en_US
dc.contributor.authorRamal M.M.en_US
dc.contributor.authorYaseen Z.M.en_US
dc.contributor.authorHossain M.S.en_US
dc.contributor.authorShahid S.en_US
dc.contributor.authorid36350315600en_US
dc.contributor.authorid6504799138en_US
dc.contributor.authorid57200533428en_US
dc.contributor.authorid56436206700en_US
dc.contributor.authorid55579596900en_US
dc.contributor.authorid57195934440en_US
dc.date.accessioned2023-05-29T07:30:59Z
dc.date.available2023-05-29T07:30:59Z
dc.date.issued2019
dc.descriptionbiochemical oxygen demand; chemical oxygen demand; dissolved oxygen; electrical conductivity; environmental assessment; hydrological modeling; physicochemical property; response surface methodology; river system; water quality; water temperature; Euphrates River; Iraq; oxygen; sulfate; water; analysis; biochemical oxygen demand; environmental monitoring; Iraq; procedures; prospective study; river; statistical model; statistics and numerical data; temperature; water pollutant; water pollution; water quality; Biological Oxygen Demand Analysis; Environmental Monitoring; Iraq; Models, Statistical; Oxygen; Prospective Studies; Rivers; Sulfates; Temperature; Water; Water Pollutants, Chemical; Water Pollution; Water Qualityen_US
dc.description.abstractSurface and ground water resources are highly sensitive aquatic systems to contaminants due to their accessibility to multiple-point and non-point sources of pollutions. Determination of water quality variables using mathematical models instead of laboratory experiments can have venerable significance in term of the environmental prospective. In this research, application of a new developed hybrid response surface method (HRSM) which is a modified model of the existing response surface model (RSM) is proposed for the first time to predict biochemical oxygen demand (BOD) and dissolved oxygen (DO) in Euphrates River, Iraq. The model was constructed using various physical and chemical variables including water temperature (T), turbidity, power of hydrogen (pH), electrical conductivity (EC), alkalinity, calcium (Ca), chemical oxygen demand (COD), sulfate (SO 4 ), total dissolved solids (TDS), and total suspended solids (TSS) as input attributes. The monthly water quality sampling data for the period 2004�2013 was considered for structuring the input-output pattern required for the development of the models. An advance analysis was conducted to comprehend the correlation between the predictors and predictand. The prediction performances of HRSM were compared with that of support vector regression (SVR) model which is one of the most predominate applied machine learning approaches of the state-of-the-art for water quality prediction. The results indicated a very optimistic modeling accuracy of the proposed HRSM model to predict BOD and DO. Furthermore, the results showed a robust alternative mathematical model for determining water quality particularly in a data scarce region like Iraq. � 2018, Springer-Verlag GmbH Germany, part of Springer Nature.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/s11356-018-3663-x
dc.identifier.epage937
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85056454924
dc.identifier.spage923
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85056454924&doi=10.1007%2fs11356-018-3663-x&partnerID=40&md5=2376a220a1eb1602b44a6b858ad64ce6
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25047
dc.identifier.volume26
dc.publisherSpringer Verlagen_US
dc.sourceScopus
dc.sourcetitleEnvironmental Science and Pollution Research
dc.titleDetermination of biochemical oxygen demand and dissolved oxygen for semi-arid river environment: application of soft computing modelsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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