Yıl: 2020 Cilt: 8 Sayı: 5 Sayfa Aralığı: 200 - 205 Metin Dili: İngilizce DOI: 10.21923/jesd.825442 İndeks Tarihi: 19-03-2021

PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM

Öz:
Wood material is a natural, sustainable, renewable and environmentally friendlymaterial that can be used in both structural and non-structural applications.However, one of the most important negative features of wood material is that it isa hygroscopic material. Heat treatment application increase dimensional stabilityof the wood material and becomes more hydrophobic. In this study, firstly, thecontact angle values of Cedar wood have been determined in the tangential andradial direction by dropping them on the surface of the wood material. Then theswelling and shrinkage amounts of the same samples were determined. TS 4084standard was used to determine the swelling and shrinkage amounts. As a result,shrinkage and swelling amounts of the samples were estimated by using artificialneural network (ANN) and Random Forest (RF) algorithm. In the estimation madeby RF and ANN methods, contact angle values were used as input. It has beendetermined that the predictions made with RF Algorithm give the most accurateresults (tangential direction, R2= 0.91, radial direction, R2= 0.97). As a result, it hasbeen determined by RF Algorithm that shrinkage and swelling values of a woodmaterial whose con-tact angle values are known can be better predicted.
Anahtar Kelime:

ISIL İŞLEM GÖRMÜŞ SEDİR ODUNU DARALMA VE GENIŞLEME DEĞERLERININ YAPAY SİNİR AĞLARI VE RASTGELE ORMAN ALGORİTMASI İLE TAHMİNİ

Öz:
Ahşap malzeme, hem yapısal hem de yapısal olmayan uygulamalarda kullanılabilen doğal, sürdürülebilir, yenilenebilir ve çevre dostu bir malzemedir. Ancak ahşap malzemenin en önemli olumsuz özelliklerinden biri higroskopik bir malzeme olmasıdır. Isıl işlem uygulaması ahşap malzemenin boyutsal stabilitesini arttırmakta ve daha hidrofobik hale getirmektedir. Bu çalışmada öncelikle, Sedir odununun temas açısı değerleri, ahşap malzeme yüzeyine damlatma ile teğet ve radyal yönde belirlenmiştir. Daha sonra aynı numunelerin genişleme ve daralma miktarları belirlenmiştir. Genişleme ve daralma miktarlarının belirlenmesinde TS 4084 standardı kullanılmıştır. Deneysel çalışma sonucunda, yapay sinir ağı (ANN) ve rastgele orman algoritması kullanılarak örneklerin daralma ve genişleme miktarları tahmin edilmiştir. Rastgele orman ve ANN yöntemleri ile yapılan tahminlerde temas açısı değerleri girdi olarak kullanılmıştır. Rastgele Orman Algoritması ile yapılan tahminlerin en doğru sonuçları verdiği tespit edilmiştir (teğet yön, R2= 0.91, radyal yön, R2= 0.97). Sonuç olarak, temas açısı değerleri bilinen bir ahşap malzemenin Rastgele Orman Algoritması ile daralma ve genişleme değerlerinin daha iyi tahmin edilebileceği belirlenmiştir.
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
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APA Kilincarslan S, ŞİMŞEK Y, İNCE M (2020). PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM. , 200 - 205. 10.21923/jesd.825442
Chicago Kilincarslan Semsettin,ŞİMŞEK Yasemin,İNCE MURAT PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM. (2020): 200 - 205. 10.21923/jesd.825442
MLA Kilincarslan Semsettin,ŞİMŞEK Yasemin,İNCE MURAT PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM. , 2020, ss.200 - 205. 10.21923/jesd.825442
AMA Kilincarslan S,ŞİMŞEK Y,İNCE M PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM. . 2020; 200 - 205. 10.21923/jesd.825442
Vancouver Kilincarslan S,ŞİMŞEK Y,İNCE M PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM. . 2020; 200 - 205. 10.21923/jesd.825442
IEEE Kilincarslan S,ŞİMŞEK Y,İNCE M "PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM." , ss.200 - 205, 2020. 10.21923/jesd.825442
ISNAD Kilincarslan, Semsettin vd. "PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM". (2020), 200-205. https://doi.org/10.21923/jesd.825442
APA Kilincarslan S, ŞİMŞEK Y, İNCE M (2020). PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM. Mühendislik Bilimleri ve Tasarım Dergisi, 8(5), 200 - 205. 10.21923/jesd.825442
Chicago Kilincarslan Semsettin,ŞİMŞEK Yasemin,İNCE MURAT PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM. Mühendislik Bilimleri ve Tasarım Dergisi 8, no.5 (2020): 200 - 205. 10.21923/jesd.825442
MLA Kilincarslan Semsettin,ŞİMŞEK Yasemin,İNCE MURAT PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM. Mühendislik Bilimleri ve Tasarım Dergisi, vol.8, no.5, 2020, ss.200 - 205. 10.21923/jesd.825442
AMA Kilincarslan S,ŞİMŞEK Y,İNCE M PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM. Mühendislik Bilimleri ve Tasarım Dergisi. 2020; 8(5): 200 - 205. 10.21923/jesd.825442
Vancouver Kilincarslan S,ŞİMŞEK Y,İNCE M PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM. Mühendislik Bilimleri ve Tasarım Dergisi. 2020; 8(5): 200 - 205. 10.21923/jesd.825442
IEEE Kilincarslan S,ŞİMŞEK Y,İNCE M "PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM." Mühendislik Bilimleri ve Tasarım Dergisi, 8, ss.200 - 205, 2020. 10.21923/jesd.825442
ISNAD Kilincarslan, Semsettin vd. "PREDICTION OF HEAT-TREATED CEDAR WOOD SWELLING AND SHRINKAGE WITH ARTIFICIAL NEURAL NETWORKS AND RANDOM FOREST ALGORITHM". Mühendislik Bilimleri ve Tasarım Dergisi 8/5 (2020), 200-205. https://doi.org/10.21923/jesd.825442