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dc.contributor.authorTiryaki, Sebahattin
dc.contributor.authorTan, Hüseyin
dc.contributor.authorBardak, Selahattin
dc.contributor.authorKankal, Murat
dc.contributor.authorNacar, Sinan
dc.contributor.authorPeker, Hüseyin
dc.date.accessioned2020-10-07T06:28:43Z
dc.date.available2020-10-07T06:28:43Z
dc.date.issued2019en_US
dc.identifier.citationTiryaki, S., Tan, H., Bardak, S., Kankal, M., Nacar, S., & Peker, H. (2019). Performance evaluation of multiple adaptive regression splines, teaching–learning based optimization and conventional regression techniques in predicting mechanical properties of impregnated wood. European Journal of Wood and Wood Products, 77(4), 645-659, DOİ:10.1007/s00107-019-01416-9.en_US
dc.identifier.urihttps://hdl.handle.net/11494/2296
dc.description.abstractUnderstanding the mechanical behaviour of impregnated wood is crucial in making a preliminary decision on the usability of such woods for structural purposes. In this paper, by considering concentration (1, 3 and 5%), pressure (1, 1.5 and 2 atm.), and time (30, 60, 90 and 120 min), an experimental study was performed, and the mechanical behaviour of impregnated wood was determined as a result of the experimental process. Multiple adaptive regression splines (MARS), teaching–learning based optimization (TLBO) algorithms and conventional regression analysis (CRA) were applied to diferent regression functions by using experimentally obtained data. The functions were checked against each other to detect the best equation for each parameter and to assess performances of MARS, TLBO and CRA methods in the prediction of mechanical properties. The experimental results showed that higher values of mechanical properties were obtained when lower concentration, pressure and time were chosen. Overall, all the functions successfully predicted the mechanical properties. However, the MARS and TLBO provided better accuracy in predicting the mechanical properties. The modeling results indicated that the MARS and TLBO are promising new methods in predicting the mechanical properties of impregnated wood. With the use of these methods, the mechanical behavior of impregnated wood could be determined with high levels of accuracy. Thus, the proposed methods may facilitate a preliminary decision concerning the usability of such woods for areas where the mechanical properties are important. Finally, the employment of MARS and TLBO algorithms by practitioners in the wood industry is encouraged and recommended for future studies.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject[No Keywords Available]en_US
dc.titlePerformance evaluation of multiple adaptive regression splines, teaching-learning based optimization and conventional regression techniques in predicting mechanical properties of impregnated wooden_US
dc.typearticleen_US
dc.relation.journalEuropean Journal of Wood and Wood Productsen_US
dc.departmentAÇÜ, Orman Fakültesien_US
dc.authorid0000-0002-7771-6993en_US
dc.identifier.volume77en_US
dc.identifier.issue4en_US
dc.identifier.startpage645en_US
dc.identifier.endpage659en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1007/s00107-019-01416-9en_US
dc.contributor.institutionauthorPeker, Hüseyinen_US


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