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| Ammunition Storage Life Prediction Method Based on Optimization Algorithm |
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| DOI：10.7643/issn.1672-9242.2023.01.002 |
| KeyWord:ammunition storage life genetic algorithms particle swarm algorithm BP neural networks support vector machines |
| Author | Institution |
| FENG Chang-lin |
Unit 92942, People's Liberation Army, Beijing , China |
| SHAO Bo-han |
Systems Engineering Research Institute of CSSC, Beijing , China |
| CHENG Yu-sen |
Naval University of Engineering, Wuhan , China |
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| Abstract: |
| The work aims to achieve the ability to predict and supplement the missing and insufficient BM drug storage failure data. First, four different prediction algorithms (GA-BP, PSO-BP, GA-SVM, and PSO-SVM) were used to predict the storage failure data of ammunition under natural storage conditions. Second, the ammunition storage life assessment model was constructed according to the least squares. At last, the life assessment model was used to calculate the corresponding storage life under different methods. Prediction of ammunition storage failure data can be achieved by all four prediction methods and optimization-free conditions. And in the specified reliability, the accuracy of GA-BP and PSO-BP predictions is lower compared to the other two methods. GA-SVM and PSO-SVM are better suited to predicting ammunition storage failure data and are more effective. |
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