ANALYSIS OF SOME TOP SURFACE TREATMENT MATERIALS WITH THE ARTIFICIAL NEURAL NETWORK METHOD

TAN H.

FRESENIUS ENVIRONMENTAL BULLETIN, vol.30, no.11A, pp.12421-12429, 2021 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 30 Issue: 11A
  • Publication Date: 2021
  • Journal Name: FRESENIUS ENVIRONMENTAL BULLETIN
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Chemical Abstracts Core, Communication Abstracts, Environment Index, Geobase, Greenfile, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Page Numbers: pp.12421-12429
  • Keywords: ANN, Boric acid, Mechanical properties, Nano-technical varnish
  • Recep Tayyip Erdoğan University Affiliated: Yes

Abstract

In this study, the effect of nano technological varnish on some mechanical properties (such as bending strength, modulus of elasticity and compressive strength) of oriental spruce (Picea orientails L. Link) wood and the effect of boric acid on mechanical properties of nano-technological varnished wood were investigated. Moreover, it was aimed to estimate bending strength, modulus of elasticity and compressive strength values of impregnated and nano-technological varnished wood material by using artificial neural network models. Nano-technological varnish increased the bending strength, modulus of elasticity and compressive strength parallel to fiber of the samples. It was found that MAPE values are low for bending strength, modulus of elasticity and compressive strength. This situation showed that artificial neural network (ANN) gives very successful results.