2020
DOI: 10.1007/s12204-020-2223-y
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Multi-Objective Optimization for Structure Crashworthiness Based on Kriging Surrogate Model and Simulated Annealing Algorithm

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Cited by 3 publications
(3 citation statements)
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“…In formula (7), μ shows the learning rate set by the BP neural network. e following formula can be obtained by combining the above contents:…”
Section: Construction Of the Obesity Monitoringmentioning
confidence: 99%
See 1 more Smart Citation
“…In formula (7), μ shows the learning rate set by the BP neural network. e following formula can be obtained by combining the above contents:…”
Section: Construction Of the Obesity Monitoringmentioning
confidence: 99%
“…Lin et al [ 6 ] proposed a heuristic solution method based on simulated annealing algorithm and then solved the marshalling problem of the railway freight transportation system. Sun et al [ 7 ] used simulated annealing algorithm to optimize the Kriging agent model, so as to realize the crashworthiness optimization of the automobile front end structure. Huang et al [ 8 ] proposed an improved simulated annealing algorithm to deal with the fixed contour plane planning problem of modern buildings.…”
Section: Introductionmentioning
confidence: 99%
“…Based on social and economic aspects, researchers examined the variables influencing the demand for car-sharing. Sun Lishan et al (2020) [2] developed the demand prediction model of the land use index and extensively examined the relationship between the demand for car-sharing and the distribution traits of the nearby land use. Pucci Paola (2021) [3] researched how metropolitan spatial patterns affect consumer demand for electric vehicles.…”
Section: Research Statusmentioning
confidence: 99%