Swarm intelligence based deep learning model via improved whale optimization algorithm and Bi-directional long short-term memory for fault diagnosis of chemical processes-Reference-Cited by-同舟云学术

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Swarm intelligence based deep learning model via improved whale optimization algorithm and Bi-directional long short-term memory for fault diagnosis of chemical processes

Published:2024-04 Issue: Volume:147 Page:227-238
ISSN:0019-0578
Container-title:ISA Transactions
language:en
Short-container-title:ISA Transactions

Author:

Ji Chunlei,Zhang Chu^ORCID,Suo Leiming,Liu Qianlong,Peng Tian

Publisher

Elsevier BV

Reference38 articles.

1. A fault diagnosis method for complex chemical process based on multi-model fusion;He;Chem Eng Res Des,2022

2. A probabilistic multivariate method for fault diagnosis of industrial processes;Yu;Chem Eng Res Des,2015

3. Fault detection and diagnosis using Bayesian network model combining mechanism correlation analysis and process data: application to unmonitored root cause variables type faults;Liu;Process Saf Environ Prot,2022

4. Spatio-temporal wind speed prediction based on Clayton Copula function with deep learning fusion;Huang;Renew Energy,2022

5. A novel fault diagnosis method for TE process based on optimal extreme learning machine;Hu;Appl Sci,2022

Cited by 1 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. A Novel Transformer Network Based on Cross–Spatial Learning and Deformable Attention for Composite Fault Diagnosis of Agricultural Machinery Bearings;Agriculture;2024-08-18

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