A Comparison of Regression, Neural Network and Fuzzy Logic Models for Estimating Chlorophyll-A Concentrations in Reservoirs

dc.authorid Chen, Ding-Geng/0000-0002-3199-8665
dc.authorwosid Chen, Ding-Geng/GRR-2103-2022
dc.contributor.author Chen, Ding-Geng
dc.contributor.author Soyupak, Selcuk
dc.date.accessioned 2024-10-06T10:57:33Z
dc.date.available 2024-10-06T10:57:33Z
dc.date.issued 2005
dc.department Atılım University en_US
dc.department-temp [Chen, Ding-Geng] Int Pacific Halibut Commiss, POB 95009, Seattle, WA 98145 USA; [Soyupak, Selcuk] Atilim Univ, Civil Engn Dept, TR-06836 Ankara, Turkey en_US
dc.description Chen, Ding-Geng/0000-0002-3199-8665 en_US
dc.description.abstract A comparison is conducted in this paper for the multiple linear regression, neural network and fuzzy logic models for their ability to estimate pseudo steady state chlorophyll-a concentrations in a very large and deep dam reservoir that exhibits high spatial and temporal variability. The utilized data set include chlorophyll-a concentrations as an indicator of primary productivity as well as several other water quality variables such as alkalinity, PO4 phosphorus, water temperature and dissolved oxygen concentrations as independent environmental variables. Using the conventional model criteria of correlation coefficient and mean square errors, the fuzzy logic model performed the best with the neural network model better than multiple linear regression model. en_US
dc.description.woscitationindex Emerging Sources Citation Index
dc.identifier.citationcount 0
dc.identifier.endpage 78 en_US
dc.identifier.issn 0972-9984
dc.identifier.issn 0973-7308
dc.identifier.issue 1 en_US
dc.identifier.startpage 65 en_US
dc.identifier.uri https://hdl.handle.net/20.500.14411/8747
dc.identifier.volume 3 en_US
dc.identifier.wos WOS:000420082000003
dc.language.iso en en_US
dc.publisher Centre Environment Social & Economic Research Publ-ceser en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Multiple linear regression model en_US
dc.subject fuzzy logic model en_US
dc.subject neural network model en_US
dc.subject dam reservoir management en_US
dc.subject eutrophication en_US
dc.title A Comparison of Regression, Neural Network and Fuzzy Logic Models for Estimating Chlorophyll-A Concentrations in Reservoirs en_US
dc.type Article en_US
dc.wos.citedbyCount 0
dspace.entity.type Publication

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