ANALYSIS AND DETECTION OF OUTLIERS AND SYSTEMATIC ERRORS IN INDUSTRIAL PLANT DATA-Reference-Cited by-同舟云学术

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ANALYSIS AND DETECTION OF OUTLIERS AND SYSTEMATIC ERRORS IN INDUSTRIAL PLANT DATA

Published:2006-12-05 Issue:3 Volume:194 Page:382-397
ISSN:0098-6445
Container-title:Chemical Engineering Communications
language:en
Short-container-title:Chemical Engineering Communications

Author:

Alves Rita M. B.¹,Nascimento Claudio A. O.¹

Affiliation:

1. a CESQ—Center for Chemical Systems Engineering, Department of Chemical Engineering , Polytechnic School, University of São Paulo , São Paulo , Brazil

Publisher

Informa UK Limited

Subject

General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/00986440600899955

Reference14 articles.

1. Gross errors detection of industrial data by neural network and cluster techniques

Cited by 4 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. Data-based design of inferential sensors for petrochemical industry;Computers & Chemical Engineering;2021-10

2. Coal Industrial Supply Chain Network and Associated Evaluation Models;Sustainability;2020-11-27

3. Designing and Testing a Chemical Demulsifier Dosage Controller in a Crude Oil Desalting Plant: An Artificial Intelligence-Based Network Approach;Chemical Engineering & Technology;2010-04-28

4. Data Reconciliation Using Neural Networks for the Determination of KLa;Computational Intelligence Techniques for Bioprocess Modelling, Supervision and Control;2009

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