Performance evaluation of multiple adaptive regression splines, teaching–learning based optimization and conventional regression techniques in predicting mechanical properties of impregnated wood
Yazarlar (6)
Türkiye
Türkiye
Türkiye
Bursa Uludağ Üniversitesi, Türkiye
Türkiye
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | EUROPEAN JOURNAL OF WOOD AND WOOD PRODUCTS |
| Dergi ISSN | 0018-3768 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Makale Dili | Türkçe |
| Basım Tarihi | 07-2019 |
| Cilt No | 77 |
| Sayı | 4 |
| Sayfalar | 645 / 659 |
| DOI Numarası | 10.1007/s00107-019-01416-9 |
| Makale Linki | http://dx.doi.org/10.1007/s00107-019-01416-9 |
| Özet |
| Understanding 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 different 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 … |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| WoS | 13 |
| Google Scholar | 18 |