Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 6
1683-1687

Soft sensor modeling of extreme learning machine based on improved particle swarm optimization

Sheng Xiaochena,b
Shi Xudonga,b
Xiong Weilia,b
a. School of Internet of Things Engineering, b. Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education, Jiangnan University, Wuxi Jiangsu 214122, China
DOI: 10.19734/j.issn.1001-3695.2018.11.0863

Abstract

Industrial processes often contain significant strong nonlinearity and time-varying behavior. Traditional ELM based soft sensor sometimes fails to make use of data information effectively and has poor prediction performance. This paper proposed an improved particle swarm optimization algorithm, which had better convergence speed and search ability than standard PSO. This algorithm used the characteristics of Gaussian distribution to update the inertia weight adaptively and changed learning factor linearly. It optimized the penalty coefficient and kernel parameter of ELM to obtain a group of optimal parameters. This algorithm was applied to soft sensor modeling for the debutanizer column process. The simulation results verify that the proposed method has good prediction accuracy and generalization performance.

Foundation Support

国家自然科学基金资助项目(61773182)
江苏高校优势学科建设工程资助项目(PAPD)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.11.0863
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 6
Section: Algorithm Research & Explore
Pages: 1683-1687
Serial Number: 1001-3695(2020)06-016-1683-05

Publish History

[2020-06-05] Printed Article

Cite This Article

盛晓晨, 史旭东, 熊伟丽. 改进粒子群优化的极限学习机软测量建模方法 [J]. 计算机应用研究, 2020, 37 (6): 1683-1687. (Sheng Xiaochen, Shi Xudong, Xiong Weili. Soft sensor modeling of extreme learning machine based on improved particle swarm optimization [J]. Application Research of Computers, 2020, 37 (6): 1683-1687. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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