Predictive modeling of milk adulteration with urea content using the gray wolf optimization algorithm and long and short-term memory network model

IF 1.1 4区化学 Q3 SPECTROSCOPY Spectroscopy Letters Pub Date : 2024-04-08 DOI:10.1080/00387010.2024.2331616

Wenjing Zhang, Kangle Fu, Heru Xue, Jiangping Liu

引用次数: 0

Abstract

Traditional methods for the determining of urea contaminants in milk, including chromatography, spectrophotometry, and electrochemical processes, have drawbacks such as long testing times and sampl...

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利用灰狼优化算法和长短期记忆网络模型建立尿素含量牛奶掺假预测模型

测定牛奶中尿素污染物的传统方法（包括色谱法、分光光度法和电化学法）存在检测时间长、采样困难等缺点。

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来源期刊

Spectroscopy Letters 物理-光谱学

CiteScore

2.90

自引率

5.90%

发文量

审稿时长

1.3 months

期刊介绍： Spectroscopy Letters provides vital coverage of all types of spectroscopy across all the disciplines where they are used—including novel work in fundamental spectroscopy, applications, diagnostics and instrumentation. The audience is intended to be all practicing spectroscopists across all scientific (and some engineering) disciplines, including: physics, chemistry, biology, instrumentation science, and pharmaceutical science.

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