摘要
研究并设计了一套电子鼻系统,并将基于生物嗅觉的模糊神经网络作为其模式识别算法。将该仿生电子鼻系统应用于芝麻油掺伪的检测中。实验结果显示,该系统在预测精度、收敛速度及运行时间上都取得了较好的效果,可为芝麻油以及其他农产品的在线动态监测及保真提供快速、有效的手段。
An bionic electronic nose was developed and fuzzy neural network based on biological olfaction was used as pattern recognition algorithms. The system was applied in the detection of adulteration in sesame oil. The results showed that the bionic electronic nose had good prediction precision,high convergent speed and less running time,and it was a fast and credible method in monitoring and dynamic detection of sesame oil or other products online.
出处
《粮食与油脂》
北大核心
2016年第6期75-77,共3页
Cereals & Oils
基金
河北省高等学校科学研究计划项目(SZ16127)
廊坊市科学技术项目(2015012010)
关键词
电子鼻
模式识别
模糊神经网络
electronic nose
pattern recognition
fuzzy neural network
