Classification of Systematic Measurement Errors within the Framework of Robust Data Reconciliation-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Classification of Systematic Measurement Errors within the Framework of Robust Data Reconciliation

Published:2017-08-17 Issue:34 Volume:56 Page:9617-9628
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Llanos Claudia E.¹,Sánchez Mabel C.¹,Maronna Ricardo A.²

Affiliation:

1. Planta Piloto de Ingeniería Química (Universidad Nacional del Sur - CONICET), Camino La Carrindanga km 7, 8000 Bahía Blanca, Argentina

2. Departamento. de Matemática, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata 1900, Argentina

Funder

Consejo Nacional de Investigaciones Científicas y Técnicas

Universidad Nacional del Sur

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.7b00726

Reference19 articles.

1. Robust Statistics

2. Simultaneous strategies for data reconciliation and gross error detection of nonlinear systems

3. Data reconciliation and gross-error detection for dynamic systems

Cited by 14 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. Estimation of feeding composition content based on novel variable sliding window method and layered data reconciliation with multiple modes;Chemometrics and Intelligent Laboratory Systems;2024-05

2. Measurement bias invariant moving horizon estimation in the presence of outliers for data reconciliation of nonlinear dynamic systems;Chemical Engineering Science;2022-05

3. Shedding Light on Data Reconciliation Techniques Applied to Analytical Chemistry;Critical Reviews in Analytical Chemistry;2021-11-07

4. A review on robust M-estimators for regression analysis;Computers & Chemical Engineering;2021-04

5. A Modified Expectation Maximization Approach for Process Data Rectification;Processes;2021-01-30

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