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19 October 2022 Street lighting system fault diagnosis research
Ken Yuan Fan, Jun Chao Zhang, Ji Hao Chang, Ze Jun Li, Qiang Fu, Jian Ning Li, Jie Zhang
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Proceedings Volume 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering; 122940E (2022) https://doi.org/10.1117/12.2639870
Event: 7th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2022), 2022, Xishuangbanna, China
Abstract
Based on the current characteristics of street lighting, the sensor data is extracted from the existing smart lighting devices, and the lighting failure prediction model of pigeon optimal BP network is built. The algorithm introduces magnetic navigation and landmark navigation in pigeon-inspired optimization into BP network, which solves the drawbacks of slow convergence and easy falling into local optimum of traditional network. The simulation results show that the algorithm can be applied to the prediction and diagnosis of urban street light illumination faults.
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Ken Yuan Fan, Jun Chao Zhang, Ji Hao Chang, Ze Jun Li, Qiang Fu, Jian Ning Li, and Jie Zhang "Street lighting system fault diagnosis research", Proc. SPIE 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 122940E (19 October 2022); https://doi.org/10.1117/12.2639870
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KEYWORDS
Neural networks
Evolutionary algorithms
Data modeling
Optimization (mathematics)
Data centers
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