Prediction of the color change of surface thermally treated wood by artificial neural network

Surface thermal treatment (STT) can achieve efficient and successful thermal modification on wood surfaces, resulting in a beautiful, natural, uniform darker color and velvety texture. This study aimed to evaluate the effect of STT on White Ash, Yellow Poplar, and Red Oak specimens using a heated press at varying temperatures and times. To enhance the material utilization, reduce the number of experiments, and optimize the process, we employed artificial neural network (ANN) to model the relationship between the provided color, treatment time, and temperature required to attain the desired color. As the ANN model can simulate the process result very fast with a high degree of accuracy ( R^2 above 0.96), it allowed us to rule off approximately 95