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Updated: Sep 13, 2025

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
10:25

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

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基于高光谱成像的朱果种类的分类预测:对智能优化算法的比较研究

Quancheng Liu1,2, Jun Zhou1,2, Zhaoyi Wu1

  • 1School of Technology, Beijing Forestry University, Beijing 100083, China.

Foods (Basel, Switzerland)
|July 29, 2025
PubMed
概括

准确的朱果品种分类至关重要. 这项研究使用超光谱成像和灰狼优化支持矢量机 (GWO-SVM) 模型与SG1st预处理,实现94.641%的质量控制准确度.

关键词:
这就是GWO GWO.在SVM中,SVM是SVM.干燥的朱果是什么意思超光谱成像技术的使用.智能优化算法 智能优化算法机器学习是机器学习.品种分类,品种分类.

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