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- Title
Fuzzy ridgelet neural network prediction model trained by improved particle swarm algorithm for maintenance decision of polypropylene plant.
- Authors
Zhao, Bin; Ren, Yi; Gao, Diankui; Xu, Lizhi; Zhang, Yuanyuan
- Abstract
The proper maintenance plan should be made for ensuring the safety and reliability of polypropylene plant and improve economic benefits of petrochemical enterprise. To meet the requirement, a novel maintenance prediction model of polypropylene plant based on fuzzy theory, ridgelet an artificial neural network is constructed. The economy and reliability models of polypropylene plant maintenance are established through comprehensively considering the reliability and economy. The basic structure of fuzzy ridgelet neural network is designed, and the training algorithm is improved through combining the traditional particle swarm algorithm and bacterial foraging algorithm, and the corresponding algorithm flow is confirmed. Finally, prediction simulation analysis is carried out using a polypropylene plant as research object, and analysis results show that the fuzzy ridgelet neural network has best prediction effect, and the optimal maintenance plan can be confirmed to ensure security and reduce maintenance cost of polypropylene plant.
- Subjects
POLYPROPYLENE; POLYOLEFINS; ALGORITHMS; NEURAL circuitry; FUZZY logic
- Publication
Quality & Reliability Engineering International, 2019, Vol 35, Issue 4, p1231
- ISSN
0748-8017
- Publication type
Article
- DOI
10.1002/qre.2456