Process prediction model for wood plastic composites pencil boards based on BP neural network

Corn straw fiber powder and high-density polyethylene as the main raw materials, polystyrene, silane and paraffin as adhesives, coupling agents and lubricants, respectively, plant fiber composite materials were prepared for the replacement osf basswood pencil board. How the mass ratios of the corn straw powder, high density polyethylene and polystyrene influence the performance of the composite pencil boards were analyzed. The process prediction model for composite pencil boards based on BP neural network was designed, whose accuracy is up to 6%.