摘要
为了寻求工业培养基有效配比，以获得Bacillus amyloliquefaciens Q-426发酵培养较大活性，根据Bacillus amyloliquefaciens Q-426摇瓶培养实验数据，以甘蔗糖蜜、豆粕粉、氯化铵、氯化钙4个培养基成份作为影响抑菌圈直径的主要因素，利用BP（Backpropagation）神经网络方法对其抑菌圈直径进行预测，获得抑菌圈直径的BP神经网络预测模型。结果表明：训练BP神经网络时，14组自变量数据中抑菌圈直径的BP神经网络拟合值与实测值的相对误差为-1．8519％～1．9231％，相对误差绝对值的平均值为1．1213％；测试BP神经网络时，3组自变量数据中抑菌圈直径的BP神经网络预测值与实测值的相对误差为-1．8519％-0．7692％，相对误差绝对值的平均值为1．1515％，说明建立的基于4个培养基成份的抑菌圈直径BP神经网络预测模型是可行的。
In order to acquire higher antimicrobial activities based on Bacillus amyloliquefaciens Q-426 fermentation, a prediction of size of inhibiting zones （SIZ） was carried out with BP neural network based on the experimental data of Bacillus amyloliquefaciens Q-426 in shake flask. Taking cane molasses, soybean meal, NH4CI and CaC12 as influence factors, the prediction model of SIZ based on BP neural network was obtained. The results show that the relative error of fitting value and predicting value of SIZ compared with the observed value for 14 groups and 3 groups of independent variables are from -1.8519 % to 1.9231% and from -1.8519 % to 0.7692 % based on BP neural network model, respectively. The average value of absolute value of relative error are 1.1213 % and 1.1515 %, respectively. Therefore, the prediction model of SIZ with BP neural network based on 4 medium compositions is doable.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2013年第9期1055-1058,共4页
Computers and Applied Chemistry
基金
大连民族学院自主科研基金项目(DC13010205)
国家大学生创新创业训练计划辽宁省创新项目(X2012028)
大连民族学院"太阳鸟"学生科研资助项目
