Prediction of Arrival Time of Pure Electric Bus Based on FA-BP Algorithm
To establish a suitable pure electric bus arrival time prediction model, this paper takes pure electric bus as the research object. Based on the analysis of the influencing factors of the arrival time of the pure electric bus, the BP neural network arrival time prediction model optimized by the fire...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2023/4320930 |
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| _version_ | 1849307139911188480 |
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| author | Yuanwen Lai Hangyu Liang Liling Huang |
| author_facet | Yuanwen Lai Hangyu Liang Liling Huang |
| author_sort | Yuanwen Lai |
| collection | DOAJ |
| description | To establish a suitable pure electric bus arrival time prediction model, this paper takes pure electric bus as the research object. Based on the analysis of the influencing factors of the arrival time of the pure electric bus, the BP neural network arrival time prediction model optimized by the firefly algorithm (FA-BP prediction model) is established by selecting vehicle type, SOC value, battery age, and time as input conditions. The model is trained and tested by using bus operation data. The root mean square error of the Kalman filter model is 0.351, of the BP neural network model is 0.059, and of the FA-BP prediction model is 0.04. The results show that the model in this paper effectively improves the prediction accuracy and has good reliability and feasibility. It can provide some theoretical references for pure electric bus operation and managers and provide some basis for improving bus reliability. |
| format | Article |
| id | doaj-art-1d298c6ab2604ffdbf19ee14fc225192 |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-1d298c6ab2604ffdbf19ee14fc2251922025-08-20T03:54:51ZengWileyJournal of Advanced Transportation2042-31952023-01-01202310.1155/2023/4320930Prediction of Arrival Time of Pure Electric Bus Based on FA-BP AlgorithmYuanwen Lai0Hangyu Liang1Liling Huang2College of Civil EngineeringCollege of Civil EngineeringFuzhou Urban and Rural Planning and Design Institute Company LimitedTo establish a suitable pure electric bus arrival time prediction model, this paper takes pure electric bus as the research object. Based on the analysis of the influencing factors of the arrival time of the pure electric bus, the BP neural network arrival time prediction model optimized by the firefly algorithm (FA-BP prediction model) is established by selecting vehicle type, SOC value, battery age, and time as input conditions. The model is trained and tested by using bus operation data. The root mean square error of the Kalman filter model is 0.351, of the BP neural network model is 0.059, and of the FA-BP prediction model is 0.04. The results show that the model in this paper effectively improves the prediction accuracy and has good reliability and feasibility. It can provide some theoretical references for pure electric bus operation and managers and provide some basis for improving bus reliability.http://dx.doi.org/10.1155/2023/4320930 |
| spellingShingle | Yuanwen Lai Hangyu Liang Liling Huang Prediction of Arrival Time of Pure Electric Bus Based on FA-BP Algorithm Journal of Advanced Transportation |
| title | Prediction of Arrival Time of Pure Electric Bus Based on FA-BP Algorithm |
| title_full | Prediction of Arrival Time of Pure Electric Bus Based on FA-BP Algorithm |
| title_fullStr | Prediction of Arrival Time of Pure Electric Bus Based on FA-BP Algorithm |
| title_full_unstemmed | Prediction of Arrival Time of Pure Electric Bus Based on FA-BP Algorithm |
| title_short | Prediction of Arrival Time of Pure Electric Bus Based on FA-BP Algorithm |
| title_sort | prediction of arrival time of pure electric bus based on fa bp algorithm |
| url | http://dx.doi.org/10.1155/2023/4320930 |
| work_keys_str_mv | AT yuanwenlai predictionofarrivaltimeofpureelectricbusbasedonfabpalgorithm AT hangyuliang predictionofarrivaltimeofpureelectricbusbasedonfabpalgorithm AT lilinghuang predictionofarrivaltimeofpureelectricbusbasedonfabpalgorithm |