Publication:
Determination of Reflectance Values of Hypericum's Leaves Under Stress Conditions Using Adaptive Network Based Fuzzy Inference System

dc.authorscopusid21743556600
dc.authorscopusid25227092700
dc.authorscopusid35279274300
dc.authorscopusid25651919200
dc.authorscopusid35781802800
dc.authorscopusid24474284100
dc.contributor.authorOdabaş, M.S.
dc.contributor.authorTemizel, K.E.
dc.contributor.authorÇalişkan, O.
dc.contributor.authorŞenyer, N.
dc.contributor.authorKayhan, Gokhan
dc.contributor.authorErgün, E.
dc.date.accessioned2020-06-21T13:59:15Z
dc.date.available2020-06-21T13:59:15Z
dc.date.issued2014
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Odabaş] Mehmet Serhat, Vocational High School of Bafra, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Temizel] Kadir Ersin, Department of Agricultural Structures and Irrigation, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Çalişkan] Ömer, Vocational High School of Bafra, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Şenyer] Nurettin, Department of Computer Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Kayhan] Gökhan, Department of Computer Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Ergün] Erhan, Department of Computer Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkeyen_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. © CTU FTS 2014.en_US
dc.identifier.doi10.14311/NNW.2014.24.004
dc.identifier.endpage87en_US
dc.identifier.issn1210-0552
dc.identifier.issn2336-4335
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-84903145115
dc.identifier.scopusqualityQ4
dc.identifier.startpage79en_US
dc.identifier.urihttps://doi.org/10.14311/NNW.2014.24.004
dc.identifier.volume24en_US
dc.identifier.wosWOS:000333141100005
dc.identifier.wosqualityQ4
dc.language.isoenen_US
dc.publisherInstitute of Computer Science Pod vodarenskou vezi 2 Prague 8, 18207en_US
dc.relation.ispartofNeural Network Worlden_US
dc.relation.journalNeural Network Worlden_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectANFISen_US
dc.subjectHypericumen_US
dc.subjectReflectanceen_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
dspace.entity.typePublication

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