Construction design based on particle group optimization algorithm
The machines exhibit an intelligence which is artificial intelligence (AI), and it is the design of intelligent agents. A system is represented by an intelligent agent who perceives its environment and the success rate is maximized by taking the action. The AI research is highly specialized and ther...
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De Gruyter
2021
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oai:doaj.org-article:f91d599dcf8b450da118b0af89a4a20c2021-12-05T14:10:51ZConstruction design based on particle group optimization algorithm2191-026X10.1515/jisys-2021-0157https://doaj.org/article/f91d599dcf8b450da118b0af89a4a20c2021-11-01T00:00:00Zhttps://doi.org/10.1515/jisys-2021-0157https://doaj.org/toc/2191-026XThe machines exhibit an intelligence which is artificial intelligence (AI), and it is the design of intelligent agents. A system is represented by an intelligent agent who perceives its environment and the success rate is maximized by taking the action. The AI research is highly specialized and there are two subfields and each communication fails often. The popular AI approaches include the traditional symbolic AI and computational intelligence. In order to optimize the seismic design of the reinforced concrete pier structure, the particle swarm optimization (PSO) algorithm and the reaction spectrum analysis method are combined; they establish a regular bridge of the design variable with cross-sectional characteristics and reinforcement ratios, with the target function. The seismic optimization design framework of the pier is transformed into a multi-objective optimization problem. Calculations show that the method can quickly obtain the optimal design parameters that meet multi-objective requirements. The improved PSO main program and the calling push-over program run time are 4.32 and 1347.56 s, respectively; the push-over program running time is 99.68% of the run time of the total program. Optimization of the seismic performance of the rear bridge pier is significantly improved and is more in line with the design method; the design method proposed in this article is more practical.Xia YingIkbal Mohammad AsifShah Mohd AsifDe Gruyterarticleparticle group optimization algorithmstructural optimizationsteel frameperformance-based seismic designreinforcement ratioscomputational intelligenceScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 1040-1053 (2021) |
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DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
particle group optimization algorithm structural optimization steel frame performance-based seismic design reinforcement ratios computational intelligence Science Q Electronic computers. Computer science QA75.5-76.95 |
| spellingShingle |
particle group optimization algorithm structural optimization steel frame performance-based seismic design reinforcement ratios computational intelligence Science Q Electronic computers. Computer science QA75.5-76.95 Xia Ying Ikbal Mohammad Asif Shah Mohd Asif Construction design based on particle group optimization algorithm |
| description |
The machines exhibit an intelligence which is artificial intelligence (AI), and it is the design of intelligent agents. A system is represented by an intelligent agent who perceives its environment and the success rate is maximized by taking the action. The AI research is highly specialized and there are two subfields and each communication fails often. The popular AI approaches include the traditional symbolic AI and computational intelligence. In order to optimize the seismic design of the reinforced concrete pier structure, the particle swarm optimization (PSO) algorithm and the reaction spectrum analysis method are combined; they establish a regular bridge of the design variable with cross-sectional characteristics and reinforcement ratios, with the target function. The seismic optimization design framework of the pier is transformed into a multi-objective optimization problem. Calculations show that the method can quickly obtain the optimal design parameters that meet multi-objective requirements. The improved PSO main program and the calling push-over program run time are 4.32 and 1347.56 s, respectively; the push-over program running time is 99.68% of the run time of the total program. Optimization of the seismic performance of the rear bridge pier is significantly improved and is more in line with the design method; the design method proposed in this article is more practical. |
| format |
article |
| author |
Xia Ying Ikbal Mohammad Asif Shah Mohd Asif |
| author_facet |
Xia Ying Ikbal Mohammad Asif Shah Mohd Asif |
| author_sort |
Xia Ying |
| title |
Construction design based on particle group optimization algorithm |
| title_short |
Construction design based on particle group optimization algorithm |
| title_full |
Construction design based on particle group optimization algorithm |
| title_fullStr |
Construction design based on particle group optimization algorithm |
| title_full_unstemmed |
Construction design based on particle group optimization algorithm |
| title_sort |
construction design based on particle group optimization algorithm |
| publisher |
De Gruyter |
| publishDate |
2021 |
| url |
https://doaj.org/article/f91d599dcf8b450da118b0af89a4a20c |
| work_keys_str_mv |
AT xiaying constructiondesignbasedonparticlegroupoptimizationalgorithm AT ikbalmohammadasif constructiondesignbasedonparticlegroupoptimizationalgorithm AT shahmohdasif constructiondesignbasedonparticlegroupoptimizationalgorithm |
| _version_ |
1718371657274359808 |