A machine learning methodology for reliability evaluation of complex chemical production systems-Reference-Cited by-同舟云学术

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A machine learning methodology for reliability evaluation of complex chemical production systems

Published:2020 Issue:34 Volume:10 Page:20374-20384
ISSN:2046-2069
Container-title:RSC Advances
language:en
Short-container-title:RSC Adv.

Author:

Zhao Fanrui¹²³⁴⁵^ORCID,Wu Jinkui¹²³⁴⁵,Zhao Yuanpei⁶⁷⁸⁹⁵,Ji Xu¹²³⁴⁵,Zhou Li¹²³⁴⁵,Sun Zhongping¹²³⁴⁵

Affiliation:

1. Department of Chemical Engineering

2. College of Chemical Engineering

3. Sichuan University

4. Chengdu 610065

5. China

6. State Key Laboratory of Power Transmission Equipment & System Security and New Technology

7. School of Electrical Engineering

8. Chongqing University

9. Chongqing

Abstract

In this article we propose a hybrid model (GRA-PSO-SVM-RF-MCRC) for the reliability evaluation of chemical production systems.

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2020/RA/C9RA09654J

Reference44 articles.

1. Deep convolutional neural network model based chemical process fault diagnosis

2. A deep belief network based fault diagnosis model for complex chemical processes

3. HSE culture in the petroleum industry: Lost in translation?

4. Study on the HSE Management at Construction Site of Oil and Gas Processing Area

5. Chemical-system reliability: a review

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1. Utilizing ResNet for enhanced quality prediction in PET production: an AI-driven approach;Journal of Polymer Engineering;2024-07-01

2. MSS principles and application;Reliability Modeling in Industry 4.0;2023

3. Deep learning for safety assessment of nuclear power reactors: Reliability, explainability, and research opportunities;Progress in Nuclear Energy;2022-09

4. Comprehensive Machine Learning-Based Model for Predicting Compressive Strength of Ready-Mix Concrete;Materials;2021-02-25

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