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Quantization of Adulteration Ratio of Raw Cow Milk by Least Squares Support Vector Machines (LS-SVM) and Visible/Near Infrared Spectroscopy

机译：最小二乘支持向量机（LS-SVM）和可见/近红外光谱法对生牛奶的掺假率进行量化

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摘要

Part 6: Support Vector Machines

机译：第6部分：支持向量机

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作者
Hsieh, Ching-Lu; Hung, Chao-Yung; Kuo, Ching-Yun;
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年度 2011
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正文语种 en
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专利

1. Application of invasive weed optimization and least square support vector machine for prediction of beef adulteration with spoiled beef based on visible near-infrared (Vis-NIR) hyperspectral imaging [J] . Zhao Hai-Tao, Feng Yao-Ze, Chen Wei, Meat Science . 2019,第MAY期

机译：入侵杂草优化和最小二乘支持向量机在可见近红外（Vis-NIR）高光谱成像预测变质牛肉掺假中的应用
2. Utilizing visible and near infrared spectroscopy based on multi-class support vector machines classification to characterize olive oil adulteration [J] . Mahdi Ghasemi-Varnamkhasti, Samaneh Amini-Pozveh, Seyed Ahmad Mireei, Agricultural Engineering International: CIGR Ejournal . 2018,第3期

机译：利用基于多类支持向量机分类的可见和近红外光谱来表征橄榄油掺假
3. Detection of adulteration by hydrolysed leather protein in infant formula based on least squares support vector machine and near-infrared spectroscopy [J] . Liu Yisen, Zhou Songbin, Han Wei, Journal of food and nutrition research . 2017,第3期

机译：基于最小二乘支持向量机和近红外光谱的婴儿配方食品中水解皮革蛋白掺假检测
4. Quantization of Adulteration Ratio of Raw Cow Milk by Least Squares Support Vector Machines (LS-SVM) and Visible/Near Infrared Spectroscopy [C] . Ching-Lu Hsieh, Chao-Yung Hung, Ching-Yun Kuo Engineering applications of neural networks . 2011

机译：最小二乘支持向量机（LS-SVM）和可见/近红外光谱法对生牛奶的掺假率进行量化
5. Optimizing sample preparation and scanning methods for component analysis of raw milk by fourier transform near infrared spectroscopy. [D] . Reuter, Anthony Joseph. 2013

机译：通过傅里叶变换近红外光谱法优化原料乳成分分析的样品制备和扫描方法。
6. Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries [O] . Sarbjit Singh, Kulwinder Singh Parmar, Sidhu Jitendra Singh Makkhan, -1

机译：ARIMA和最小二乘支持向量机（LS-SVM）模型用于预测受灾最严重国家中SARS-CoV-2确诊病例的研究
7. Quantization of Adulteration Ratio of Raw Cow Milk by Least Squares Support Vector Machines (LS-SVM) and Visible/Near Infrared Spectroscopy [O] . Hsieh, Ching-Lu, Hung, Chao-Yung, Kuo, Ching-Yun 2011

机译：最小二乘支持向量机（LS-SVM）和可见/近红外光谱法对生牛奶的掺假率进行量化

Quantization of Adulteration Ratio of Raw Cow Milk by Least Squares Support Vector Machines (LS-SVM) and Visible/Near Infrared Spectroscopy

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