Açık Akademik Arşiv Sistemi

SEPARATION OF STREAM FLOW INTO COMPONENTS THROUGH THE USE OF A CO-ACTIVE NEURO FUZZY INFERENCE SYSTEM (CANFIS)

Show simple item record

dc.contributor.authors Sengorur, B; Dede, C; Dogan, E
dc.date.accessioned 2020-03-06T08:07:34Z
dc.date.available 2020-03-06T08:07:34Z
dc.date.issued 2014
dc.identifier.citation Sengorur, B; Dede, C; Dogan, E (2014). SEPARATION OF STREAM FLOW INTO COMPONENTS THROUGH THE USE OF A CO-ACTIVE NEURO FUZZY INFERENCE SYSTEM (CANFIS). FRESENIUS ENVIRONMENTAL BULLETIN, 23, 2288-2279
dc.identifier.issn 1018-4619
dc.identifier.uri https://doi.org/
dc.identifier.uri https://hdl.handle.net/20.500.12619/67133
dc.description.abstract In this study, the usability of a Co-Active Neuro-Fuzzy Inference System (CANFIS) as an alternative to the Digital Filtering (DFM) and United Kingdom Institute of Hydrology (UKIH) mathematical methods, which are frequently used for separating total stream flow into surface and base flow, was examined. Surface flow and base flow values determined from the daily average flow data of the Aksu Stream in the Melen Basin of Turkey's Northern Black Sea Region through the use of DFM (alpha = 0,830) and UKIH (N = 5) methods were used as the training and test data of CANFIS. The applications trained through DFM and UKIH were, respectively, titled as CANFIS(DFM) and CANFIS(UKIH). Performances of all of the methods used were compared by error analysis and the examination of base flow indexes (BFI). Obtained flow values and BFI results showed that the surface flow and base flow estimations of all methods are significantly similar, and that the base flow values provided by the UKIH and CANFIS(UKIH) methods were bigger than those obtained from the DFM and CANFIS(DFM) methods as reported in the studies included in the literature. In addition, it was understood that in both CANFIS(DFM) and CANFIS(UKIH) methods, the effects of the methods used for training were fairly limited on the surface flow (R-2=0,9709) and base flow (R-2=0,9765) test values. In conclusion, the study demonstrated that CANFIS can be used in the determination of surface flow and base flow without needing parameters required by the DFM and UKIH methods, namely, recession coefficient and number of members in minimum groups.
dc.language English
dc.publisher PARLAR SCIENTIFIC PUBLICATIONS (P S P)
dc.subject Separation of stream flow components; surface flow; base flow; CANFIS
dc.title SEPARATION OF STREAM FLOW INTO COMPONENTS THROUGH THE USE OF A CO-ACTIVE NEURO FUZZY INFERENCE SYSTEM (CANFIS)
dc.type Article
dc.identifier.volume 23
dc.identifier.startpage 2279
dc.identifier.endpage 2288
dc.contributor.department Sakarya Üniversitesi/Mühendislik Fakültesi/Çevre Mühendisliği Bölümü
dc.contributor.saüauthor Şengörür, Bülent
dc.contributor.saüauthor Dede, Cemile
dc.contributor.saüauthor Doğan, Emrah
dc.relation.journal FRESENIUS ENVIRONMENTAL BULLETIN
dc.identifier.wos WOS:000349805100010
dc.identifier.eissn 1610-2304
dc.contributor.author Şengörür, Bülent
dc.contributor.author Dede, Cemile
dc.contributor.author Doğan, Emrah


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record