电子鼻运用智能识别算法分析果汁中酒精混合物
emre ordukaya bekir karlik
abstract
the aim of this study is to analyze the raw data collected from a fruit juice–alcohol mixture (a fruit juice–alcohol mixture and a fruit juice–multiple alcohol mixture) and the halal authentication of a fruit juice–alcohol mixture with electronic nose. machine learning techniques such as naïve bayesian classifier, k‐nearest neiors (k‐nn), linear discriminant analysis (lda), decision tree, artificial neural network (ann), and support vector machine (svm) were used to classify the feature of these collected raw data. there are three types of classification: the first one is a fruit juice and an alcohol mixture type; the second is a fruit juice and multiple alcohol mixture types, and the third is a halal authentication of a fruit juice and alcohol mixture. we aimed at making cocktails with more successful results on the first two types of classification in the work. also, we focused on halal authentication of fruit juice–alcohol mixture in the third classification
本研究的目的是分析从果汁-酒精混合物(果汁-酒精混合物和果汁-多元酒精混合物)中收集的原始数据，以及带有电子鼻的果汁-酒精混合物的清真认证。采用纳维贝叶斯分类器、k近邻(k-nn)、线性判别分析(lda)、决策树、人工神经网络(ann)和支持向量机(svm)等机器学习技术对采集到的原始数据进行特征分类。有三种分类：种是果汁和酒精混合物类型；第二种是果汁和多种酒精混合物类型；第三种是果汁和酒精混合物的清真认证。我们的目标是使鸡尾酒在前两类分类上取得更为成功的结果。此外，我们重点研究了第三类果汁-酒精混合物的清真认证。