[1]高珏,李海森,徐超,等.基于模糊隶属度的近红外光谱模型鲁棒性分析[J].哈尔滨工程大学学报,2015,(03):312-316.[doi:10.3969/j.issn.1006-7043.201312026]
 GAO Jue,LI Haisen,XU Chao,et al.Robustness analysis of near infrared spectroscopy model using fuzzy membership[J].hebgcdxxb,2015,(03):312-316.[doi:10.3969/j.issn.1006-7043.201312026]
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基于模糊隶属度的近红外光谱模型鲁棒性分析
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2015年03期
页码:
312-316
栏目:
出版日期:
2015-03-25

文章信息/Info

Title:
Robustness analysis of near infrared spectroscopy model using fuzzy membership
作者:
高珏123 李海森12 徐超12 朱培逸3
1. 哈尔滨工程大学 水声工程学院, 黑龙江 哈尔滨 150001;
2. 哈尔滨工程大学 水声技术重点实验室, 黑龙江 哈尔滨 150001;
3. 常熟理工学院 电气与自动化工程学院, 江苏 常熟 215500
Author(s):
GAO Jue123 LI Haisen12 XU Chao12 ZHU Peiyi3
1. College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China;
2. Science and Technology on Underwater Acoustic Laboratory, Harbin Engineering University, Harbin 150001, China;
3. College of Electric and Automatic Engineering, Changshu Institute of Technology, Changshu 215500, China
关键词:
鲁棒性模糊隶属度近红外光谱建模噪声数据域描述
分类号:
TP273.4
DOI:
10.3969/j.issn.1006-7043.201312026
文献标志码:
A
摘要:
针对近红外光谱模型存在的鲁棒性问题,在模型建立时引入模糊隶属度,提出了一种自动生成模糊隶属度的方法.建立光谱样本的数据域描述函数,引入信任因子和舍弃因子,通过映射关系得到模糊隶属度函数,参数寻优后自动生成每个样本的模糊隶属度.在此基础上建立了基于FSVM的苹果糖度回归模型.试验结果表明,对比常规的MLR、PLSR和SVM模型,FSVM模型在训练样本变化和高斯噪声、乘性噪声、基线漂移、基线倾斜和波长漂移这5种噪声的分别作用下表现出最佳的性能.模糊隶属度的引入提高了近红外光谱模型的泛化能力和抗噪能力,改善了模型的鲁棒性.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2013-12-26;改回日期:。
基金项目:苏州市科技计划资助项目(SYN201109).
作者简介:高珏(1981-),男,博士研究生;李海森(1962-),男,教授,博士生导师.
通讯作者:李海森,E-mail:hsenli@126.com.
更新日期/Last Update: 2015-06-16