RELIABILITY PREDICTION OF DRYER BASED ON IMPROVED PSO＿BP NEURAL NETWORK (MT)
When the BP neural network model is used to predict the reliability of the grain dryer, the model has problems such as slow convergence speed and easy to fall into local optimum. An improved particle swarm algorithm is used to optimize the BP neural network model and establish the PSO＿BP neural netw...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Strength
2023-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.02.035 |
| _version_ | 1797767611158626304 |
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| author | WEN ChangJun CHEN Zhe SHAO MingYing CHEN Li XU Yun Fei |
| author_facet | WEN ChangJun CHEN Zhe SHAO MingYing CHEN Li XU Yun Fei |
| author_sort | WEN ChangJun |
| collection | DOAJ |
| description | When the BP neural network model is used to predict the reliability of the grain dryer, the model has problems such as slow convergence speed and easy to fall into local optimum. An improved particle swarm algorithm is used to optimize the BP neural network model and establish the PSO＿BP neural network The reliability prediction model of grain dryer is compared with MAERMSEMAPE index obtained by BP network model and GA＿BP network model. The research results show that when the improved PSO＿BP network model is used for forecasting, the three indicators are reduced by 0.051 8, 0.047 9 and 28.04% respectively compared with the BP network model; the three indicators are reduced by 0.000 4, 0.000 2 and 0.61% respectively compared with the GA＿BP network model, Which shows that it has smaller errors and better predictive ability. The methods and ideas for realizing accurate prediction of the reliability of grain dryers are provided. |
| first_indexed | 2024-03-12T20:41:18Z |
| format | Article |
| id | doaj.art-8c754c264a474419a6246b9c84051aef |
| institution | Directory Open Access Journal |
| issn | 1001-9669 |
| language | zho |
| last_indexed | 2024-03-12T20:41:18Z |
| publishDate | 2023-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj.art-8c754c264a474419a6246b9c84051aef2023-08-01T07:55:15ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692023-01-0150450836350503RELIABILITY PREDICTION OF DRYER BASED ON IMPROVED PSO＿BP NEURAL NETWORK (MT)WEN ChangJunCHEN ZheSHAO MingYingCHEN LiXU Yun FeiWhen the BP neural network model is used to predict the reliability of the grain dryer, the model has problems such as slow convergence speed and easy to fall into local optimum. An improved particle swarm algorithm is used to optimize the BP neural network model and establish the PSO＿BP neural network The reliability prediction model of grain dryer is compared with MAERMSEMAPE index obtained by BP network model and GA＿BP network model. The research results show that when the improved PSO＿BP network model is used for forecasting, the three indicators are reduced by 0.051 8, 0.047 9 and 28.04% respectively compared with the BP network model; the three indicators are reduced by 0.000 4, 0.000 2 and 0.61% respectively compared with the GA＿BP network model, Which shows that it has smaller errors and better predictive ability. The methods and ideas for realizing accurate prediction of the reliability of grain dryers are provided.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.02.035Grain dryer;Particle swarm algorithm;BP neural network;Reliability prediction |
| spellingShingle | WEN ChangJun CHEN Zhe SHAO MingYing CHEN Li XU Yun Fei RELIABILITY PREDICTION OF DRYER BASED ON IMPROVED PSO＿BP NEURAL NETWORK (MT) Jixie qiangdu Grain dryer;Particle swarm algorithm;BP neural network;Reliability prediction |
| title | RELIABILITY PREDICTION OF DRYER BASED ON IMPROVED PSO＿BP NEURAL NETWORK (MT) |
| title_full | RELIABILITY PREDICTION OF DRYER BASED ON IMPROVED PSO＿BP NEURAL NETWORK (MT) |
| title_fullStr | RELIABILITY PREDICTION OF DRYER BASED ON IMPROVED PSO＿BP NEURAL NETWORK (MT) |
| title_full_unstemmed | RELIABILITY PREDICTION OF DRYER BASED ON IMPROVED PSO＿BP NEURAL NETWORK (MT) |
| title_short | RELIABILITY PREDICTION OF DRYER BASED ON IMPROVED PSO＿BP NEURAL NETWORK (MT) |
| title_sort | reliability prediction of dryer based on improved pso bp neural network mt |
| topic | Grain dryer;Particle swarm algorithm;BP neural network;Reliability prediction |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.02.035 |
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