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dc.contributor.authorOdabas, Mehmet Serhat
dc.contributor.authorTemizel, Kadir Ersin
dc.contributor.authorCaliskan, Omer
dc.contributor.authorSenyer, Nurettin
dc.contributor.authorKayhan, Gokhan
dc.contributor.authorErgun, Erhan
dc.date.accessioned2020-06-21T13:59:15Z
dc.date.available2020-06-21T13:59:15Z
dc.date.issued2014
dc.identifier.issn1210-0552
dc.identifier.urihttps://doi.org/10.14311/NNW.2014.24.004
dc.identifier.urihttps://hdl.handle.net/20.500.12712/15478
dc.descriptionWOS: 000333141100005en_US
dc.description.abstractThe effects of water stress and salt levels on hypericum's leaves were examined on greenhouse-grown plants of Hypericum perforatum L. by spectral reflectance. Salt levels and irrigation levels were applied 0, 1, 2.5 and 4 deci Siemens per meter (dS/m), 80%, 100% and 120% respectively. Adaptive Network based Fuzzy Inference System (ANFIS) was performed to estimate the effects of water stress and salt levels on spectral reflectance. As a result of ANFIS, it was found that there was close relationship between actual and predicted reflectance values in Hypericum perforatum L. leaves. Performance of ANFIS was examined under different numbers of epoch and rules. On the other hand, RMSE, correlation and analysis time values were found as outputs. Correlation was 99%. The estimation of optimal ANFIS model was determined in 3*3*3 number of rules with 400 epochs.en_US
dc.language.isoengen_US
dc.publisherAcad Sciences Czech Republic, Inst Computer Scienceen_US
dc.relation.isversionof10.14311/NNW.2014.24.004en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectReflectanceen_US
dc.subjectANFISen_US
dc.subjecthypericumen_US
dc.subjectsalten_US
dc.subjectwater stressen_US
dc.titleDetermination of Reflectance Values of Hypericum'S Leaves Under Stress Conditions Using Adaptive Network Based Fuzzy Inference Systemen_US
dc.typearticleen_US
dc.contributor.departmentOMÜen_US
dc.identifier.volume24en_US
dc.identifier.issue1en_US
dc.identifier.startpage79en_US
dc.identifier.endpage87en_US
dc.relation.journalNeural Network Worlden_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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