1. 太原理工大学电气与动力工程学院
2. 山西格盟中美清洁能源研发中心有限公司
纸质出版:2023
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任超, 叶泽甫, 程兰, 等. 基于测地线流式核的隐空间多工况软测量建模[J]. 传感器与微系统, 2023,(10):28-31.
任超, 叶泽甫, 程兰, 等. 基于测地线流式核的隐空间多工况软测量建模[J]. 传感器与微系统, 2023,(10):28-31. DOI: 10.13873/J.1000-9787(2023)10-0028-04.
针对工业过程中工况变化后的新工况缺乏标记样本构建预测模型,原有软测量模型预测失准的问题,研究了一种基于迁移潜在特征学习的多工况软测量方法。首先,利用测地线流式核框架对多工况下分布不匹配的过程数据进行域适应;然后,通过特征迁移后的历史工况样本与标签变量获取映射矩阵,将多工况迁移样本投影至隐空间;最后,利用支持向量机(SVM)建模。通过田纳西伊斯曼(TE)过程仿真实验的标签预测结果表明本文方法的有效性。
基于BP神经网络的秸秆发酵过程乙醇浓度软测量方法[J]. 马凤英;于文志.传感器与微系统,2021(07)
基于混合蛙跳算法的极限学习机软测量建模[J]. 孙顺远;周乾.传感器与微系统,2021(05)
循环流化床入炉垃圾热值软测量[J]. 尤海辉;马增益;唐义军;王月兰;郑林;俞钟;吉澄军.浙江大学学报(工学版),2017(06)
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A novel geodesic flow kernel based domain adaptation approach for intelligent fault diagnosis under varying working condition[J]. Zhongwei Zhang;Huaihai Chen;Shunming Li;Zenghui An;Jinrui Wang.Neurocomputing,2020
Mixture modeling for industrial soft sensor application based on semi-supervised probabilistic PLS[J]. Junhua Zheng;Zhihuan Song.Journal of Process Control,2019
Soft sensor modeling with a selective updating strategy for Gaussian process regression based on probabilistic principle component analysis[J]. Weili Xiong;Xudong Shi.Journal of the Franklin Institute,2018
A Framework and Modeling Method of Data-Driven Soft Sensors Based on Semisupervised Gaussian Regression[J]. Yan, Weiwu;Guo, Pengju;Tian, Yu;Gao, Jianjun.Industrial & Engineering Chemistry Research,2016
Optimal online soft sensor for product quality monitoring in propylene polymerization process[J]. Zhong Cheng;Xinggao Liu.Neurocomputing,2015
Data-driven soft sensor development based on deep learning technique[J]. Chao Shang;Fan Yang;Dexian Huang;Wenxiang Lyu.Journal of Process Control,2014
A Bayesian inference based two-stage support vector regression framework for soft sensor development in batch bioprocesses[J]. Jie Yu.Computers and Chemical Engineering,2012
Data-driven prediction of the product formation in industrial 2-keto-L-gulonic acid fermentation[J]. Lei Cui;Ping Xie;Junwei Sun.Computers & Chemical Engineering: An International Journal of Computer Applications in Chemical Engineering,2012
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