Prediction Of The Thermal Conductivities Of Wood Based On An Intelligent Algorithm

For thermal comfort and energy-saving performance, a floor-heating method is superior to conventional heating modes, e.g., radiator, fan coil, etc. The floor-heating method has been developed to be a primary indoor heating form. Wood is the most common floor surface material. Due to the anisotropy of wood, it is difficult to obtain a general theoretical formula for its thermal physical properties. In this paper, intelligent algorithms were adopted to predict thermal conductivities of wood. First, the study elaborated frequently used testing methods of thermal conductivity. Next, 130 types of common wood species were measured to form a database of thermal properties. With this database, intelligent algorithms were used to make predictions. For the thermal conductivity predictions that were conducted with support vector machine, the degree of fit between the predicted results and the measured results was not less than 0.87 (k-fold validation). This study validated the feasibility of the usage of the intelligent algorithm for the research and prediction of the thermal conductivities of wood.