中文摘要：

以聚乙烯醋酸乙烯酯（EVA）添加质量分数、甘油添加质量分数、Na HCO3添加质量分数为3个输入量,以淀粉/EVA复合发泡材料熔体的黏度值为输出量,建立了3层BP（back propagation）神经网络模型,并通过毛细管流变仪对复合发泡材料的熔体黏度进行测试,将其正交试验结果作为样本进行训练。研究结果表明,该BP神经网络模型能较为准确地预测复合发泡材料的流变性能;同时发现,随着EVA添加质量分数的增加,复合发泡材料的熔体黏度增加;而随着甘油添加质量分数的增加和Na HCO3添加质量分数的增加,所得复合发泡材料的熔体黏度均下降。

英文摘要：

Using the mass ratio of ethylene-vinyl acetate to EVA, glycerol content and NaHCO3 content as the input parameters, the viscosity as the output parameters, a 3-layer BP （back propagation） neural network was established. The melt viscosity of composite foaming material was tested by capillary rheometer, while the results were taken as samples to forecast the properties of starch foaming materials. The results showed that the BP neural network could predict the properties with fairly good accuracy. Meanwhile, the viscosity of foaming material increased with the increase of EVA content, the viscosity of foaming material decreased with the increase of glycerol content and NaHCO3 content.