食品工业科技2017，Vol.38Issue(5)：289-292,4.DOI:10.13386/j.issn1002-0306.2017.05.046
GA-BP神经网络及其在液体乳安全评价中的应用
GA-BP neural network and its application in safety evaluation of liquid milk
摘要
Abstract
The initial weights and thresholds of back propagation (BP) neural network were optimized by genetic algorithm (GA) to accelerate the network convergence and improve the prediction precision.The liquid milk in dairy products was used as the experimental material to establish the safety evaluation index system.The GA-BP neural network was used as the evaluation model to fit the daily data of liquid milk.The convergence rate and the fitting degree of the model were verified by the test data.The results showed that GA-BP was more stable than BP neural network and could converge quickly,and the simulation error of GA-BP neural network was smaller.When the number of nodes was 9,GA-BP neural network had the best fitting effect to liquid milk,and the prediction precision was high.So GA-BP neural network was a feasible method to evaluate the safety of liquid milk.关键词
遗传算法/BP神经网络/液体乳/食品安全评价Key words
genetic algorithm/BP neural network/liquid milk products/evaluation of food safety分类
轻工纺织引用本文复制引用
姜同强,任叶..GA-BP神经网络及其在液体乳安全评价中的应用[J].食品工业科技,2017,38(5):289-292,4.基金项目
国家科技支撑计划“电子溯源的食品安全风险评估关键技术研究与应用”(2015BAK36B04) （2015BAK36B04）
北京市科技计划项目(Z161100001616004) （Z161100001616004）
2016年研究生科研能力提升计划项目资助. （）
