Semi-supervised echo state network with temporal–spatial graph regularization for dynamic soft sensor modeling of industrial processes
Author:
Publisher
Elsevier BV
Subject
Applied Mathematics,Control and Systems Engineering,Electrical and Electronic Engineering,Computer Science Applications,Instrumentation
Reference54 articles.
1. Refining data-driven soft sensor modeling framework with variable time reconstruction;Yao;J Process Control,2020
2. A survey on deep learning for data-driven soft sensors;Sun;IEEE Trans Ind Inf,2021
3. Dual-layer feature extraction based soft sensor methods and applications to industrial polyethylene processes;Liu;Comput Chem Eng,2021
4. Multiple adaptive mechanisms for data-driven soft sensors;Bakirov;Comput Chem Eng,2017
5. Soft sensor modeling method based on semisupervised deep learning and its application to wastewater treatment plant;Yan;Ind Eng Chem Res,2020
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Twinning quality sensors in wastewater treatment process via optimized echo state network-based soft sensors;Applied Soft Computing;2024-10
2. A holistic global-local stochastic configuration network modeling framework with antinoise awareness for efficient semi-supervised regression;Information Sciences;2024-03
3. Semi-Supervised Soft Sensor Modeling Based on Ensemble Learning With Pseudolabel Optimization;IEEE Transactions on Instrumentation and Measurement;2024
4. DualLSTM: A novel key-quality prediction for a hierarchical cone thickener;Control Engineering Practice;2023-08
5. Temporospatial graph attention networks with applications for industrial dynamic soft sensor modeling;SCIENTIA SINICA Technologica;2023-06-01
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