The Machine Learning Life Cycle in Chemical Operations – Status and Open Challenges-Reference-Cited by-同舟云学术

The Machine Learning Life Cycle in Chemical Operations – Status and Open Challenges

Published:2021-11-10 Issue:12 Volume:93 Page:2063-2080
ISSN:0009-286X
Container-title:Chemie Ingenieur Technik
language:en
Short-container-title:Chemie Ingenieur Technik

Author:

Gärtler Marco¹,Khaydarov Valentin²,Klöpper Benjamin¹,Urbas Leon²

Affiliation:

1. ABB Corporate Research Center Wallstadter Straße 59 68526 Ladenburg Germany

2. Technische Universität Dresden Professur für Prozessleittechnik 01062 Dresden Germany

Funder

Bundesministerium für Wirtschaft und Energie

Publisher

Wiley

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cite.202100134

Reference187 articles.

1. S.Amershi A.Begel C.Bird R.DeLine H.Gall E.Kamar N. Nagappan B.Nushi T.Zimmermann inProc. of the 2019 IEEE/ACM 41st Int. Conf. on Software Engineering: Software Engineering in Practice IEEE Piscataway NJ2019.

2. R.Ashmore R.Calinescu C.Paterson Assuring the Machine Learning Lifecycle: Desiderata Methods and Challenges arXiv2019.https://arxiv.org/abs/1905.04223

3. S.Studer T. B.Bui C.Drescher A.Hanuschkin L.Winkler S. Peters K.‐R.Mueller Towards CRISP‐ML(Q): A Machine Learning Process Model with Quality Assurance Methodology arXiv2020.https://arxiv.org/abs/2003.05155

4. Data-Driven Mode Identification and Unsupervised Fault Detection for Nonlinear Multimode Processes

Cited by 16 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. 70 Jahre Verfahrenstechnik an der TU Dresden;Chemie Ingenieur Technik;2023-10-06

2. Development of a Modular Automation Framework for Data-Driven Modeling and Optimization of Coating Formulations;2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA);2023-09-12

3. Artificial Intelligence‐based Module Type Package‐compatible Smart Sensors in the Process Industry;Chemie Ingenieur Technik;2023-08-09

4. Technical Debt Management in Industrial ML - State of Practice and Management Model Proposal;2023 IEEE 21st International Conference on Industrial Informatics (INDIN);2023-07-18

5. Image‐Based Flow Regime Recognition in Aerated Stirred Tanks Using Deep Transfer Learning;Chemie Ingenieur Technik;2023-05-10