<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In this paper, controlling and optimizing against the earthquake by using genetic algorithm is investigated. In this paper, a new approach for selecting optimal accelerograph and scaling them for dynamic time history analysis is presented by the binary genetic algorithm and natural numbers, in order to achieve the mean response spectrum, which has a proper matching and a short distance with the target spectrum and indicates the expected earthquake of the site. Because of the difference in the nature of accelerograph and the scale coefficients, the genetic algorithm presented in this paper, is hybrid (has two chromosomes). The proposed algorithm is capable of constructing a new generation of people from a series of infinitesimal earth movement records, in a process where natural selection, mating, mutation takes place, and creates a new generation of people and continues this process until a person with desirable qualities is obtained. One of the most important factors in the accuracy and efficiency of these programs is the correct estimation of their parameters. If these parameters are correctly calculated, the difference between the mean response spectrum and the spectrum of the plot will be greatly reduced. Due to the relatively large number of these parameters, the use of trial and error-based methods largely relies on user skills, the proposed hybrid genetic algorithm program can overcome this defect. The program has two genomes that run simultaneously and provide close answers to the optimal answer. The program itself is able to provide the user with a range of optimal coefficients and crossing values and mutations of each chromosome.</p></abstract>

In this paper, controlling and optimizing against the earthquake by using genetic algorithm is investigated. In this paper, a new approach for selecting optimal accelerograph and scaling them for dynamic time history analysis is presented by the binary genetic algorithm and natural numbers, in order to achieve the mean response spectrum, which has a proper matching and a short distance with the target spectrum and indicates the expected earthquake of the site. Because of the difference in the nature of accelerograph and the scale coefficients, the genetic algorithm presented in this paper, is hybrid (has two chromosomes). The proposed algorithm is capable of constructing a new generation of people from a series of infinitesimal earth movement records, in a process where natural selection, mating, mutation takes place, and creates a new generation of people and continues this process until a person with desirable qualities is obtained. One of the most important factors in the accuracy and efficiency of these programs is the correct estimation of their parameters. If these parameters are correctly calculated, the difference between the mean response spectrum and the spectrum of the plot will be greatly reduced. Due to the relatively large number of these parameters, the use of trial and error-based methods largely relies on user skills, the proposed hybrid genetic algorithm program can overcome this defect. The program has two genomes that run simultaneously and provide close answers to the optimal answer. The program itself is able to provide the user with a range of optimal coefficients and crossing values and mutations of each chromosome.

Control and Optimization Against Earthquake by Using Genetic Algorithm

Islamic Azad University Central Tehran Branch

Journal of Applied Engineering Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Control and Optimization Against Earthquake by Using Genetic Algorithm"}

In this paper, controlling and optimizing against the earthquake by using genetic algorithm is investigated. In this paper, a new approach for selecting...

Control and Optimization Against Earthquake by Using Genetic Algorithm

Online veröffentlicht: 20. Aug. 2018

Seitenbereich: 73 - 78

Eingereicht: 07. Jan. 2018

Akzeptiert: 13. Feb. 2018

DOI: https://doi.org/10.2478/jaes-2018-0010

Schlüsselwörter
Time history analysis, Response spectrum, Plan spectrum, Genetic Algorithm, Hybrid Algorithm

© 2018 K. Tajziehchi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Control and Optimization Against Earthquake by Using Genetic Algorithm

Online veröffentlicht: 20. Aug. 2018

Seitenbereich: 73 - 78

Eingereicht: 07. Jan. 2018

Akzeptiert: 13. Feb. 2018

DOI: https://doi.org/10.2478/jaes-2018-0010

SchlüsselwörterTime history analysis, Response spectrum, Plan spectrum, Genetic Algorithm, Hybrid Algorithm

© 2018 K. Tajziehchi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Time history analysis, Response spectrum, Plan spectrum, Genetic Algorithm, Hybrid Algorithm