【摘要】 为探讨基于BP神经网络模型预测化妆品色彩配方的可行性,以口红为研究对象,按不同比例色素制备100个样本。采用节点数均为15个的2层隐含层、1层输出层的3层网络结构,通过Matlab R2016a软件构建BP神经网络模型,形成颜色RGB参数与口红色素质量配比间的非线性映射关系。在训练次数为10 000次,学习率为0.5时,各色素误差参数均小于0.6,预测配方成品与真实配方成品无明显色差。基于BP神经网络模型的化妆品配色方法,可以直接给出色彩配方,为配色工程师提供了一种快速简单的参考工具。更多还原

【Abstract】 To explore the feasibility of prediction of color formulas of cosmetics based on BP neural network model, one hundred lipstick samples of different proportions of pigments were prepared. The BP neural network model was constructed by MATLAB R2016 a software, which was composed of two hidden layers with 15 nodes and one output layer with three network structures. The nonlinear mapping relationship between the RGB parameters and the mass ratio of lipstick pigments were formed. When the training times were 10 000 and the learning rate was 0.5, the color error parameters were all less than 0.6, and there was no significant color difference between the predicted formula and the real formula. Hence the color matching method based on BP neural network model could directly generate the color formula and provide a quick and simple reference tool for color engineers.更多还原