Research on berth occupancy prediction model based on attention mechanism
To solve the problem that the berth occupancy prediction accuracy decreases while the prediction step was increasing, a berth occupancy prediction model based on an attention mechanism was proposed, which was the multivariate time pattern information obtained by convolutional neural networks (CNN).T...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2020-12-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436X.2020241/ |
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| _version_ | 1841539314598543360 |
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| author | Zhurong WANG Wei XUE Yabang NIU Ying’an CUI Qindong SUN Xinhong HEI |
| author_facet | Zhurong WANG Wei XUE Yabang NIU Ying’an CUI Qindong SUN Xinhong HEI |
| author_sort | Zhurong WANG |
| collection | DOAJ |
| description | To solve the problem that the berth occupancy prediction accuracy decreases while the prediction step was increasing, a berth occupancy prediction model based on an attention mechanism was proposed, which was the multivariate time pattern information obtained by convolutional neural networks (CNN).The characteristic information was learned by the model training, and the sequence with higher correlation was assigned a larger learning weight, so that the highly correlated features output from the decoder could be used to predict the target sequence.Data sets of multiple parking lot were adopted to test the model.The test results show that the proposed model can estimate the real value well when the step length of berth occupancy prediction reaches 36.The prediction accuracy and stability of the model are improved compared with long short-term memory (LSTM) model. |
| format | Article |
| id | doaj-art-e03597255b0f4a18950742261b0acab0 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2020-12-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-e03597255b0f4a18950742261b0acab02025-01-14T07:21:23ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2020-12-014118219259739387Research on berth occupancy prediction model based on attention mechanismZhurong WANGWei XUEYabang NIUYing’an CUIQindong SUNXinhong HEITo solve the problem that the berth occupancy prediction accuracy decreases while the prediction step was increasing, a berth occupancy prediction model based on an attention mechanism was proposed, which was the multivariate time pattern information obtained by convolutional neural networks (CNN).The characteristic information was learned by the model training, and the sequence with higher correlation was assigned a larger learning weight, so that the highly correlated features output from the decoder could be used to predict the target sequence.Data sets of multiple parking lot were adopted to test the model.The test results show that the proposed model can estimate the real value well when the step length of berth occupancy prediction reaches 36.The prediction accuracy and stability of the model are improved compared with long short-term memory (LSTM) model.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436X.2020241/time series predictionberth occupancy predictionattention mechanismsequence-to-sequence model |
| spellingShingle | Zhurong WANG Wei XUE Yabang NIU Ying’an CUI Qindong SUN Xinhong HEI Research on berth occupancy prediction model based on attention mechanism Tongxin xuebao time series prediction berth occupancy prediction attention mechanism sequence-to-sequence model |
| title | Research on berth occupancy prediction model based on attention mechanism |
| title_full | Research on berth occupancy prediction model based on attention mechanism |
| title_fullStr | Research on berth occupancy prediction model based on attention mechanism |
| title_full_unstemmed | Research on berth occupancy prediction model based on attention mechanism |
| title_short | Research on berth occupancy prediction model based on attention mechanism |
| title_sort | research on berth occupancy prediction model based on attention mechanism |
| topic | time series prediction berth occupancy prediction attention mechanism sequence-to-sequence model |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436X.2020241/ |
| work_keys_str_mv | AT zhurongwang researchonberthoccupancypredictionmodelbasedonattentionmechanism AT weixue researchonberthoccupancypredictionmodelbasedonattentionmechanism AT yabangniu researchonberthoccupancypredictionmodelbasedonattentionmechanism AT yingancui researchonberthoccupancypredictionmodelbasedonattentionmechanism AT qindongsun researchonberthoccupancypredictionmodelbasedonattentionmechanism AT xinhonghei researchonberthoccupancypredictionmodelbasedonattentionmechanism |