Detecting Unauthorized Movement of Radioactive Material Packages in Transport with an Adam-Optimized BP Neural Network Model
The rapid expansion of nuclear technology across various sectors due to global economic growth has led to a substantial rise in the transportation of radioactive materials. The International Atomic Energy Agency (IAEA) estimates that approximately 20 million shipments of radioactive materials occur...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
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| Series: | Science and Technology of Nuclear Installations |
| Online Access: | http://dx.doi.org/10.1155/2023/6363270 |
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| _version_ | 1832547958735765504 |
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| author | Panpan Jiang Xiaohua Yang Yaping Wan Tiejun Zeng Mingxing Nie Chaofeng Wang Yu Mao Zhenghai Liu |
| author_facet | Panpan Jiang Xiaohua Yang Yaping Wan Tiejun Zeng Mingxing Nie Chaofeng Wang Yu Mao Zhenghai Liu |
| author_sort | Panpan Jiang |
| collection | DOAJ |
| description | The rapid expansion of nuclear technology across various sectors due to global economic growth has led to a substantial rise in the transportation of radioactive materials. The International Atomic Energy Agency (IAEA) estimates that approximately 20 million shipments of radioactive materials occur annually. In this context, ensuring the safety and security of radioactive material transportation is of significant importance. IAEA’s “Security of Radioactive Materials in Transport” (Nuclear Security Series No. 9-G) mandates that an effective transport security system should provide immediate detection of any unauthorized removal of the packages. In the present study, an innovative Adam-optimized BP neural network model is developed for detecting unauthorized movements of radioactive material packages. To analyze the performance of the proposed algorithm, numerous experiments were conducted. The results demonstrate that the proposed method achieves a 99.17% accuracy rate in detecting unauthorized movements of radioactive materials, with a missed alarm rate of 0.72% and a false alarm rate of 0.1%. This method also enables real-time detection of unauthorized removal of radioactive materials and effectively enhances the security of radioactive materials during transport to reduce the risks of theft, loss, diversion, or sabotage. |
| format | Article |
| id | doaj-art-f91f9c609e2d4605a0aba09d347ef55b |
| institution | Kabale University |
| issn | 1687-6083 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Science and Technology of Nuclear Installations |
| spelling | doaj-art-f91f9c609e2d4605a0aba09d347ef55b2025-02-03T06:42:55ZengWileyScience and Technology of Nuclear Installations1687-60832023-01-01202310.1155/2023/6363270Detecting Unauthorized Movement of Radioactive Material Packages in Transport with an Adam-Optimized BP Neural Network ModelPanpan Jiang0Xiaohua Yang1Yaping Wan2Tiejun Zeng3Mingxing Nie4Chaofeng Wang5Yu Mao6Zhenghai Liu7School of Nuclear Science and TechnologyIntelligent Nuclear Security Technology LaboratoryIntelligent Nuclear Security Technology LaboratoryIntelligent Nuclear Security Technology LaboratoryIntelligent Nuclear Security Technology LaboratoryIntelligent Nuclear Security Technology LaboratoryIntelligent Nuclear Security Technology LaboratoryIntelligent Nuclear Security Technology LaboratoryThe rapid expansion of nuclear technology across various sectors due to global economic growth has led to a substantial rise in the transportation of radioactive materials. The International Atomic Energy Agency (IAEA) estimates that approximately 20 million shipments of radioactive materials occur annually. In this context, ensuring the safety and security of radioactive material transportation is of significant importance. IAEA’s “Security of Radioactive Materials in Transport” (Nuclear Security Series No. 9-G) mandates that an effective transport security system should provide immediate detection of any unauthorized removal of the packages. In the present study, an innovative Adam-optimized BP neural network model is developed for detecting unauthorized movements of radioactive material packages. To analyze the performance of the proposed algorithm, numerous experiments were conducted. The results demonstrate that the proposed method achieves a 99.17% accuracy rate in detecting unauthorized movements of radioactive materials, with a missed alarm rate of 0.72% and a false alarm rate of 0.1%. This method also enables real-time detection of unauthorized removal of radioactive materials and effectively enhances the security of radioactive materials during transport to reduce the risks of theft, loss, diversion, or sabotage.http://dx.doi.org/10.1155/2023/6363270 |
| spellingShingle | Panpan Jiang Xiaohua Yang Yaping Wan Tiejun Zeng Mingxing Nie Chaofeng Wang Yu Mao Zhenghai Liu Detecting Unauthorized Movement of Radioactive Material Packages in Transport with an Adam-Optimized BP Neural Network Model Science and Technology of Nuclear Installations |
| title | Detecting Unauthorized Movement of Radioactive Material Packages in Transport with an Adam-Optimized BP Neural Network Model |
| title_full | Detecting Unauthorized Movement of Radioactive Material Packages in Transport with an Adam-Optimized BP Neural Network Model |
| title_fullStr | Detecting Unauthorized Movement of Radioactive Material Packages in Transport with an Adam-Optimized BP Neural Network Model |
| title_full_unstemmed | Detecting Unauthorized Movement of Radioactive Material Packages in Transport with an Adam-Optimized BP Neural Network Model |
| title_short | Detecting Unauthorized Movement of Radioactive Material Packages in Transport with an Adam-Optimized BP Neural Network Model |
| title_sort | detecting unauthorized movement of radioactive material packages in transport with an adam optimized bp neural network model |
| url | http://dx.doi.org/10.1155/2023/6363270 |
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