STRUCTURE RELIABILITY CALCULATION METHOD BASED ON IMPROVED NEURAL NETWORK
Aiming at the problems that traditional BP neural network surrogate model had deficiency of fitting accuracy and computational efficiency, the Mind Evolutionary Algorithm was used to optimize BP neural network and an improved BP neural network surrogate model reliability calculation method was propo...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2021-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2021.06.013 |
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| _version_ | 1841535929556140032 |
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| author | LI YongHua CHEN Peng TIAN ZongRui CHEN ZhiHao |
| author_facet | LI YongHua CHEN Peng TIAN ZongRui CHEN ZhiHao |
| author_sort | LI YongHua |
| collection | DOAJ |
| description | Aiming at the problems that traditional BP neural network surrogate model had deficiency of fitting accuracy and computational efficiency, the Mind Evolutionary Algorithm was used to optimize BP neural network and an improved BP neural network surrogate model reliability calculation method was proposed. Firstly, the Mind Evolutionary Algorithm was used to optimize the weights and thresholds of BP neural network to obtain the optimal initial value. Secondly, the Bayesian Regularization algorithm was used to train the optimized neural network to establish MEA-BR-BP neural network surrogate model and verify the effectiveness of the improved surrogate model used test function. Finally, the reliability calculation results were calculated with the Monte Carlo method. The results show that the proposed method improves the fitting accuracy and gives consideration to the calculation efficiency, which verifies the superiority and feasibility of the proposed method. |
| format | Article |
| id | doaj-art-3e4459a8411a4402a747f8dd6528809c |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2021-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-3e4459a8411a4402a747f8dd6528809c2025-01-15T02:25:12ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692021-01-01431359136530612514STRUCTURE RELIABILITY CALCULATION METHOD BASED ON IMPROVED NEURAL NETWORKLI YongHuaCHEN PengTIAN ZongRuiCHEN ZhiHaoAiming at the problems that traditional BP neural network surrogate model had deficiency of fitting accuracy and computational efficiency, the Mind Evolutionary Algorithm was used to optimize BP neural network and an improved BP neural network surrogate model reliability calculation method was proposed. Firstly, the Mind Evolutionary Algorithm was used to optimize the weights and thresholds of BP neural network to obtain the optimal initial value. Secondly, the Bayesian Regularization algorithm was used to train the optimized neural network to establish MEA-BR-BP neural network surrogate model and verify the effectiveness of the improved surrogate model used test function. Finally, the reliability calculation results were calculated with the Monte Carlo method. The results show that the proposed method improves the fitting accuracy and gives consideration to the calculation efficiency, which verifies the superiority and feasibility of the proposed method.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2021.06.013BP neural networkSurrogate modelMind evolutionary algorithmReliability analysisBogie frame |
| spellingShingle | LI YongHua CHEN Peng TIAN ZongRui CHEN ZhiHao STRUCTURE RELIABILITY CALCULATION METHOD BASED ON IMPROVED NEURAL NETWORK Jixie qiangdu BP neural network Surrogate model Mind evolutionary algorithm Reliability analysis Bogie frame |
| title | STRUCTURE RELIABILITY CALCULATION METHOD BASED ON IMPROVED NEURAL NETWORK |
| title_full | STRUCTURE RELIABILITY CALCULATION METHOD BASED ON IMPROVED NEURAL NETWORK |
| title_fullStr | STRUCTURE RELIABILITY CALCULATION METHOD BASED ON IMPROVED NEURAL NETWORK |
| title_full_unstemmed | STRUCTURE RELIABILITY CALCULATION METHOD BASED ON IMPROVED NEURAL NETWORK |
| title_short | STRUCTURE RELIABILITY CALCULATION METHOD BASED ON IMPROVED NEURAL NETWORK |
| title_sort | structure reliability calculation method based on improved neural network |
| topic | BP neural network Surrogate model Mind evolutionary algorithm Reliability analysis Bogie frame |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2021.06.013 |
| work_keys_str_mv | AT liyonghua structurereliabilitycalculationmethodbasedonimprovedneuralnetwork AT chenpeng structurereliabilitycalculationmethodbasedonimprovedneuralnetwork AT tianzongrui structurereliabilitycalculationmethodbasedonimprovedneuralnetwork AT chenzhihao structurereliabilitycalculationmethodbasedonimprovedneuralnetwork |