RETRACTED ARTICLE: Hybrid recurrent Laguerre-orthogonal-polynomials neural network control with modified particle swarm optimization application for V-belt continuously variable transmission system
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-015-2053-2.pdf
Reference51 articles.
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2. Patra JC et al (2009) Laguerre neural network-based smart sensors for wireless sensor networks. In: Proceedings of the IEEE instrumentation and measurement technology conference, Singapore, pp 832–837
3. Tseng CY et al (2009) Dynamic simulation model for hybrid electric scooters. In: IEEE international symposium on industrial electronics, Seoul, Korea, pp 1464–1469
4. Lin CH et al (2010) Hybrid recurrent fuzzy neural network control for permanent magnet synchronous motor applied in electric scooter. In: 6th international power electronics conference, Sapporo, Japan, pp 1371–1376
5. Angeline PJ (1998) Evolutionary optimization verses particle swarm optimization: philosophy and the performance difference. Lect Notes Comput Sci 1447:600–610
Cited by 8 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. Retracted: Hybrid Recurrent Laguerre‐Orthogonal‐Polynomial NN Control System Applied in V‐Belt Continuously Variable Transmission System Using Particle Swarm Optimization;Mathematical Problems in Engineering;2024-01
2. CS-RNN: efficient training of recurrent neural networks with continuous skips;Neural Computing and Applications;2022-06-24
3. The novel learning solutions to nonlinear differential models on a semi-infinite domain;Engineering with Computers;2022-02-17
4. Expression of Concern to: Composite recurrent Laguerre orthogonal polynomials neural network dynamic control for continuously variable transmission system using altered particle swarm optimization;Nonlinear Dynamics;2021-02-22
5. Retraction Note: Hybrid recurrent Laguerre-orthogonal-polynomials neural network control with modified particle swarm optimization application for V-belt continuously variable transmission system;Neural Computing and Applications;2021-01-28
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