A semi‐supervised JITL paradigm based on manifold regularization for online soft sensor development

Author:

Zhou Junxi1,Li Xu1ORCID,Shao Weiming1ORCID,Zhao Dongya1

Affiliation:

1. Department of Chemical Equipment and Control Engineering, College of New Energy China University of Petroleum (East China) Qingdao China

Abstract

AbstractJust‐in‐time learning (JITL) is often used for soft measurements of nonlinear time‐varying processes due to its desirable properties. Nevertheless, most existing JITL methods utilize only limited labeled data, ignoring abundant information of plentiful unlabeled data, which prevents the JITL‐based soft sensors from achieving the best performance. To address this issue, this paper proposes a semi‐supervised JITL paradigm based on manifold regularization, denoted as MRSsJITL. The MRSsJITL could effectively use the information of unlabeled data to make up for the deficiency of supervised JITL. Then, a weighted spatial‐temporal similarity metric is developed to calculate the relevance between samples more accurately. The performance of the MRSsJITL is assessed using both numerical example and actual industrial process. The results demonstrate that, compared with the conventional JITL approaches, the MRSsJITL can efficiently improve the predictive accuracy.

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Wiley

Subject

Waste Management and Disposal,Renewable Energy, Sustainability and the Environment,General Chemical Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3