Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning
With the rapid development of intelligent transportation, intelligent algorithms and path planning have become effective methods to relieve traffic pressure. Intelligent algorithm can realize the priority selection mode in realizing traffic optimization efficiency. However, there is local optimizati...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2020/8647820 |
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| _version_ | 1850233425640816640 |
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| author | Shijin Li Fucai Wang |
| author_facet | Shijin Li Fucai Wang |
| author_sort | Shijin Li |
| collection | DOAJ |
| description | With the rapid development of intelligent transportation, intelligent algorithms and path planning have become effective methods to relieve traffic pressure. Intelligent algorithm can realize the priority selection mode in realizing traffic optimization efficiency. However, there is local optimization in intelligence and it is difficult to realize global optimization. In this paper, the antilearning model is used to solve the problem that the gray wolf algorithm falls into local optimization. The positions of different wolves are updated. When falling into local optimization, the current position is optimized to realize global optimization. Extreme Learning Machine (ELM) algorithm model is introduced to accelerate Improved Gray Wolf Optimization (IGWO) optimization and improve convergence speed. Finally, the experiment proves that IGWO-ELM algorithm is compared in path planning, and the algorithm has an ideal effect and high efficiency. |
| format | Article |
| id | doaj-art-0c2a5540ecdf4d6896f8d1bfc6bafa6e |
| institution | OA Journals |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-0c2a5540ecdf4d6896f8d1bfc6bafa6e2025-08-20T02:02:55ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2020-01-01202010.1155/2020/86478208647820Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route PlanningShijin Li0Fucai Wang1Academic Affairs Office, Yunnan University of Finance and Economics, Kunming, Yunnan 650221, ChinaYunnan Business Information Engineering School, Kunming, Yunnan 650000, ChinaWith the rapid development of intelligent transportation, intelligent algorithms and path planning have become effective methods to relieve traffic pressure. Intelligent algorithm can realize the priority selection mode in realizing traffic optimization efficiency. However, there is local optimization in intelligence and it is difficult to realize global optimization. In this paper, the antilearning model is used to solve the problem that the gray wolf algorithm falls into local optimization. The positions of different wolves are updated. When falling into local optimization, the current position is optimized to realize global optimization. Extreme Learning Machine (ELM) algorithm model is introduced to accelerate Improved Gray Wolf Optimization (IGWO) optimization and improve convergence speed. Finally, the experiment proves that IGWO-ELM algorithm is compared in path planning, and the algorithm has an ideal effect and high efficiency.http://dx.doi.org/10.1155/2020/8647820 |
| spellingShingle | Shijin Li Fucai Wang Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning Discrete Dynamics in Nature and Society |
| title | Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning |
| title_full | Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning |
| title_fullStr | Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning |
| title_full_unstemmed | Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning |
| title_short | Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning |
| title_sort | research on optimization of improved gray wolf optimization extreme learning machine algorithm in vehicle route planning |
| url | http://dx.doi.org/10.1155/2020/8647820 |
| work_keys_str_mv | AT shijinli researchonoptimizationofimprovedgraywolfoptimizationextremelearningmachinealgorithminvehiclerouteplanning AT fucaiwang researchonoptimizationofimprovedgraywolfoptimizationextremelearningmachinealgorithminvehiclerouteplanning |