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Optimal design of magnetorheological damper with multiple axial fluid flow channels using BP neural network and particle swarm optimization methodologies
Research article (International Journal of Applied Electromagnetics and Mechanics, 2021) · cited 16× · AI/ML
Optimal design of magnetorheological damper with multiple axial fluid flow channels using BP neural network and particle swarm optimization methodologies
Summary
Optimal design of magnetorheological damper with multiple axial fluid flow channels using BP neural network and particle swarm optimization methodologies is a scholarly article[1].
Key Facts
Optimal design of magnetorheological damper with multiple axial fluid flow channels using BP neural network and particle swarm optimization methodologies's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Optimal design of magnetorheological damper with multiple axial fluid flow channels using BP neural network and particle swarm optimization methodologies. Retrieved May 24, 2026, from https://4ort.xyz/entity/optimal-design-of-magnetorheological-damper-with-multiple-axial-fluid-flow-channels-using-bp-neural-network-and-particle
MLA“Optimal design of magnetorheological damper with multiple axial fluid flow channels using BP neural network and particle swarm optimization methodologies.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/optimal-design-of-magnetorheological-damper-with-multiple-axial-fluid-flow-channels-using-bp-neural-network-and-particle.
BibTeX@misc{4ortxyz_optimal-design-of-magnetorheological-damper-with-multiple-axial-fluid-flow-channels-using-bp-neural-network-and-particle_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Optimal design of magnetorheological damper with multiple axial fluid flow channels using BP neural network and particle swarm optimization methodologies}}, year = {2026}, url = {https://4ort.xyz/entity/optimal-design-of-magnetorheological-damper-with-multiple-axial-fluid-flow-channels-using-bp-neural-network-and-particle}, note = {Accessed: 2026-05-24}}
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