scholarly journals RBF networks trained by genetic algorithm appiled in active control of noise and vibration

2004 ◽  
Vol 25 (1) ◽  
pp. 109-111 ◽  
Author(s):  
Huamin Yu ◽  
Haichao Zhu ◽  
Yin Shi
1999 ◽  
Author(s):  
Daniel Fiore ◽  
Richard L. Gentilman ◽  
Robert Torri ◽  
Brian H. Houston ◽  
Robert D. Corsaro

2008 ◽  
Vol 2008.17 (0) ◽  
pp. 167-170
Author(s):  
Tsutomu KAIZUKA ◽  
Kimihiko NAKANO ◽  
Nobuo TANAKA

2020 ◽  
pp. 107754632093346
Author(s):  
Ali Banaei ◽  
Javad Alamatian

This study focuses on a new active control method by improving specification of a well-known intelligent numerical search method, that is the genetic algorithm. The proposed scheme modifies the specifications of the common genetic algorithm by using two strategies. First, a new constrained objective function is proposed. Then, a procedure is designed for evaluating and reducing time delay in control process. These procedures lead to a new generation of the genetic algorithm, which is more reliable. For verifying the efficiency of the proposed method, vibrations of several structures are controlled, and results are compared with other well-known methods such as the common genetic algorithm, linear quadratic regulator, and equivalent critical damping. Numerical results clearly prove the accuracy and efficiency of the proposed control process in comparison with other methods.


Author(s):  
Ronald Coleman ◽  
Paul J. Remington

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