A new model based on principal component regression-random forest for analyzing and predicting the physical and mechanical properties of particleboard

The physical and mechanical properties are key indexes for determining the quality of particleboards. For this reason, a study on evaluating particleboard via new method has considerable value. Thus, based principal component regression (PCR) analysis random forest (RF) is proposed in paper. First, problems requiring resolution described after analyzing production process parameters as well particleboard. Then, an prediction models PCR RF established. On basis method, that affect various determined. Based model built from previously determined properties. Finally, through experimental analysis, effectiveness verified. This work was able to determine relationship between properties, which can help improve practical industrial manufacturing effectivity.