scholarly journals Research on multi-parameter correction of vibration system based on genetic Algorithm

2021 ◽  
Vol 1750 ◽  
pp. 012016
Author(s):  
Shihao He ◽  
Cheng Zhou ◽  
Cungui Yu
Keyword(s):  
Genetic Algorithm ◽  
Vibration System ◽  
Parameter Correction

Identification of a Nonlinear Vibration System Using Simulated Annealing, Genetic Algorithm and Programming

1999 ◽  
Author(s):  
Lubomir Sláma ◽  
Mojmir Balátě ◽  
Jiří Krejsa ◽  
Jan Slavík
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Genetic Programming ◽  
Nonlinear Vibration ◽  
Vibration Isolation ◽  
Vibration System ◽  
Isolation System ◽  
Simulated Annealing Genetic Algorithm ◽  
Damping Characteristics ◽  
Nonlinear Vibration System

Abstract Application of genetic algorithm and genetic programming to identification of a nonlinear vibration system is presented. Both the theoretical groundwork and experimental results are included. The genetic algorithm is used for identification of parameters of nonlinear stiffness and friction damping characteristics of a single-degree-of-freedom model of a vibration isolation system. The genetic programming is used for identification of a functional form and parameters of a load-deflection characteristic of a rubber isolator. Obtained results from computational experiments are presented and discussed. Results of GA are compared to results obtained by using a simulated annealing method.

Calculation of Nature Frequency for Ship’s Tail Shaft Flexural Vibration Based on Genetic Algorithm

2010 ◽  
Vol 160-162 ◽  
pp. 319-323
Author(s):  
Xiao Jun Jia
Keyword(s):  
Genetic Algorithm ◽  
Transfer Matrix Method ◽  
Flexural Vibration ◽  
Mathematic Model ◽  
Engineering Calculation ◽  
Frequency Equation ◽  
Vibration System ◽  
Initial Value ◽  
System A ◽  
Nature Frequency

Analysis of the nature frequency of flexural vibration is vital to be able to provide effective shock absorption for a ship’s tail shaft. The paper built mathematic model of ship’s tail shaft flexural vibration by transfer matrix method, and put forward an effective method for calculating the natural frequency of vibration system: a genetic algorithm (GA). Through example calculation compared with Prohl method under conditions bearing isotropic supporting, the result showed that the method can meet the requirements of engineering calculation, and overcome the disadvantage that initial value of calculation is difficult to be obtained with other methods. Then the method has advantage especially when the degrees of frequency equation increase.

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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