| Summary: In this study, it was aimed to determine the synergistic effects of some multi-functional compounds (artificial antioxidants, GRAS compounds and nano-oxides) in wood protection, to model and optimize the obtained data. For this purpose, the study was carried out by dividing into three main parts. The important findings/results obtained were also examined under three main headings. In the first part, the impregnation process was applied using 14 different chemicals with only Scotch pine wood samples, and then the most suitable chemicals were selected from each of the 3 groups by making physical, chemical and biological tests of the woods and considering the cost. In the second part, single, double and triple variations of 1.0% concentrations of the selected chemicals and scotch pine and beech samples were impregnated and the synergistic effect was investigated by making biological tests of the woods. In the third part, impregnation solutions with single, double and triple variations were prepared using two different concentrations (0.5% and 1.0%) of the selected chemicals, and Scotch pine and beech samples were impregnated. The data obtained from some physical, biological and mechanical tests of woods after impregnation were modeled with multiple regression and artificial neural network methods and the best models were selected. The selected best models were optimized according to 8 different objective functions determined using the ant lion algorithm. After the study consisting of three parts, the usability of artificial intelligence methods in the wood protection industry by saving time, chemicals and labor has been revealed.
Key Words: GRAS compound, impregnation, modeling, nano-oxide, synergistic effect, artificial antioxidant, multi objective optimization |
