人工神经网络对芦苇笋酒糟中糠醛提取条件的建模
徐力斌 1徐梅 1李冬生 1周明全 2丁佑铭 2胡中立 2汪超1
作者信息
- 1. 湖北省协同创新中心; 湖北省食品发酵工程技术研究中心，湖北 武汉 430068
- 2. 武汉大学莲藕中心，湖北 武汉 430072
- 折叠
摘要
在本研究中，应用多层感知器神经网络和径向基函数(RBF)网络对芦苇笋酒糟中糠醛提取建模。人工神经网络模型用于芦苇笋酒糟和从回归分析得到从中提取糠醛的结果的比较。适当的提取条件，保证芦苇笋酒糟中糠醛的最大提取量。这项研究为白酒的生产提供了理论依据。
Abstract
In the present study, a multi-layer perception neural network and radial basis function (RBF) network were used to model of extract form Common reed liquor lees of furfural content. Artificial neural network were used to model extract furfural from Common reed liquor lees and comparison was also made with the results obtained from a regression analysis. The appropriate extraction conditions can guarantee the maximum of extract from Common reed liquor lees. This work can provide a theoretical basis for the production of liquor.
关键词
人工神经网络/多层感知器神经网络/径向基函数网络/芦苇笋酒糟/糠醛Key words
artificial neural network/a multi-layer perception neural network/radial basis function network/Common reed liquor lees/furfural引用本文复制引用
基金项目
国家科技支撑计划(2012BAD31B08)
出版年
2014
NETL
NSTL
万方数据