农业机械学报2017，Vol.48Issue(5)：335-342,8.DOI:10.6041/j.issn.1000-1298.2017.05.042
基于RSM和BP-AdaBoost-GA的红茶发酵性能参数优化
Parameter Optimization of Black Tea Fermentation Machine Based on RSM and BP-AdaBoost-GA
摘要
Abstract
Fermentation is the key procedure in processing of congou black tea,which directly decides the quality and flavor of tea products.Fermentation experiments were conducted on a novel drum-type fermentation machine as the platform,the performance parameters of fermentation machine were clarified.Methodologically,with dimensionless comprehensive scores as a measure of fermentation quality,response surface methodology (RSM) and back-propagation adaptive boosting based genetic algorithm (BP-AdaBoost-GA) were used separately to optimize three parameters (fermentation temperature x1,fermentation time x2,rotational interval x3) that affect fermentation quality.Also the optimizing effects of RSM and BP-AdaBoost-GA were compared.Results showed that the importance degrees of the three parameters ranked as x1 ＞x3 ＞x2.With RSM at x1 =25℃,x2 =150 min and x3 =20 min,the predicted and actual values of comprehensive scores were 0.863 and 0.856,respectively,showing relative error of 0.8％.With BP-AdaBoost-GA at x1 =27℃,x2 =170 min and x3 =25 min,the predicted and actual values of comprehensive scores were 0.871 and 0.868,respectively,showing relative error of 0.3％.When the BP-AdaBoost had seven nodes in the hidden layer and a prediction error threshold of 0.25,its determination coefficient was greater than that of RSM (0.994 vs 0.988),and it had lower root mean square error of prediction (RMSEP) of 0.017 and residual predictive deviation (RPD) equaled to 18.456.Both RSM and BP-AdaBoost-GA were feasible for optimization of fermentation parameters.However,the fitting ability of RSM was limited because it was based on quadratic polynomial regression,while the fitting ability over experimental data was limited.The algorithm combining improved neural network and GA had higher global extremum prediction ability and higher accuracy.Thus,it can be concluded that even though RSM was the most widely used method for fermentation parameter optimization,BP-AdaBoost-GA methodology may present a better alternative.In the meantime,the rotation function had both advantages and disadvantages on the fermentation quality of black tea,moderate rotation and mixing material can enhance the quality of black tea and shorten the fermentation time.关键词
红茶发酵/参数优化/AdaBoost算法/遗传算法Key words
black tea fermentation/parameter optimization/AdaBoost algorithm/genetic algorithm分类
轻工纺织引用本文复制引用
董春旺,赵杰文,朱宏凯,袁海波,叶阳,陈全胜..基于RSM和BP-AdaBoost-GA的红茶发酵性能参数优化[J].农业机械学报,2017,48(5):335-342,8.基金项目
国家自然科学基金项目(31271875)、浙江省自然科学基金项目(Y16C160009)和浙江省重点研发计划项目(2015C02001) （31271875）
