Enhancing transportation network intelligence through visual scene feature clustering analysis with 3D sensors and adaptive fuzzy control
The complex environments and unpredictable states within transportation networks have a significant impact on their operations. To enhance the level of intelligence in transportation networks, we propose a visual scene feature clustering analysis method based on 3D sensors and adaptive fuzzy control...
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2024-12-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-2564.pdf |
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| _version_ | 1850242358484926464 |
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| author | Jing Xu |
| author_facet | Jing Xu |
| author_sort | Jing Xu |
| collection | DOAJ |
| description | The complex environments and unpredictable states within transportation networks have a significant impact on their operations. To enhance the level of intelligence in transportation networks, we propose a visual scene feature clustering analysis method based on 3D sensors and adaptive fuzzy control to address the various complex environments encountered. Firstly, we construct a feature extraction framework for visual scenes using 3D sensors and employ a series of feature processing operators to repair cracks and noise in the images. Subsequently, we introduce a feature aggregation approach based on an adaptive fuzzy control algorithm to carefully screen the preprocessed features. Finally, by designing a similarity matrix for the transportation network environment, we obtain the recognition results for the current environment and state. Experimental results demonstrate that our method outperforms competitive approaches with a mean average precision (mAP) value of 0.776, serving as a theoretical foundation for visual scene perception in transportation networks and enhancing their level of intelligence. |
| format | Article |
| id | doaj-art-63cbff46623a405fa7254dac63d69f6a |
| institution | OA Journals |
| issn | 2376-5992 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj-art-63cbff46623a405fa7254dac63d69f6a2025-08-20T02:00:18ZengPeerJ Inc.PeerJ Computer Science2376-59922024-12-0110e256410.7717/peerj-cs.2564Enhancing transportation network intelligence through visual scene feature clustering analysis with 3D sensors and adaptive fuzzy controlJing XuThe complex environments and unpredictable states within transportation networks have a significant impact on their operations. To enhance the level of intelligence in transportation networks, we propose a visual scene feature clustering analysis method based on 3D sensors and adaptive fuzzy control to address the various complex environments encountered. Firstly, we construct a feature extraction framework for visual scenes using 3D sensors and employ a series of feature processing operators to repair cracks and noise in the images. Subsequently, we introduce a feature aggregation approach based on an adaptive fuzzy control algorithm to carefully screen the preprocessed features. Finally, by designing a similarity matrix for the transportation network environment, we obtain the recognition results for the current environment and state. Experimental results demonstrate that our method outperforms competitive approaches with a mean average precision (mAP) value of 0.776, serving as a theoretical foundation for visual scene perception in transportation networks and enhancing their level of intelligence.https://peerj.com/articles/cs-2564.pdf3D sensorAdaptive fuzzy controlFeature aggregation |
| spellingShingle | Jing Xu Enhancing transportation network intelligence through visual scene feature clustering analysis with 3D sensors and adaptive fuzzy control PeerJ Computer Science 3D sensor Adaptive fuzzy control Feature aggregation |
| title | Enhancing transportation network intelligence through visual scene feature clustering analysis with 3D sensors and adaptive fuzzy control |
| title_full | Enhancing transportation network intelligence through visual scene feature clustering analysis with 3D sensors and adaptive fuzzy control |
| title_fullStr | Enhancing transportation network intelligence through visual scene feature clustering analysis with 3D sensors and adaptive fuzzy control |
| title_full_unstemmed | Enhancing transportation network intelligence through visual scene feature clustering analysis with 3D sensors and adaptive fuzzy control |
| title_short | Enhancing transportation network intelligence through visual scene feature clustering analysis with 3D sensors and adaptive fuzzy control |
| title_sort | enhancing transportation network intelligence through visual scene feature clustering analysis with 3d sensors and adaptive fuzzy control |
| topic | 3D sensor Adaptive fuzzy control Feature aggregation |
| url | https://peerj.com/articles/cs-2564.pdf |
| work_keys_str_mv | AT jingxu enhancingtransportationnetworkintelligencethroughvisualscenefeatureclusteringanalysiswith3dsensorsandadaptivefuzzycontrol |