基于BP神经网络的木材质量评价

摘要

At present, the production process of furniture is gradually approaching to batching and mechanization. However, the quality of mahogany wood has always been a concern for the furniture industry. Therefore, the quality evaluation of wood has always been the focus of furniture manufacturing research. In this paper, the quality evaluation model of mahogany wood is established by BP neural network, and the appropriate evaluation index is selected and verified by the sample data of the case. Compared with the weighted average method, the results show that the proposed three-layer BP neural network model has a certain feasibility and practical significance in the quality evaluation of wood.%目前木材家具的生产过程在逐步向批量化、机械化趋近,但木材的质量一直是家具产业需要关注的问题,因此对木材的质量评价一直是家具制造业研究的重点.本文利用BP神经网络建立木材的质量评价模型,选择合适的评价指标,并通过案例的样本数据进行验证.测试结果与加权平均法比较,得出构建的3层BP神经网络模型应用于木材质量评价中具有一定的可行性与现实意义.