Abstract
After investigation and analysis, this paper studies deep learning to solve the automatic analysis and identification of massive unstructured media data in the power system. In terms of feature extraction, based on the Alexnet model, two independent CNN models are proposed to extract the characteristics of power equipment. In terms of recognition algorithm, the advantages of traditional machine learning methods are combined with the advantages of random forests. Intelligent identification algorithm for power equipment combined with CNN.
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Acknowledgments
This work was financially supported by the science and technology project to State Grid Corporation “Research on Intelligent Reconfiguration and Cognitive Technology of Complex Dynamic Operating Environment Based on Deep Vision.”
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He, Z. et al. (2020). Research on Intelligent Identification Method of Power Equipment Based on Deep Learning. In: Kountchev, R., Patnaik, S., Shi, J., Favorskaya, M. (eds) Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology. Smart Innovation, Systems and Technologies, vol 179. Springer, Singapore. https://doi.org/10.1007/978-981-15-3863-6_15
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DOI: https://doi.org/10.1007/978-981-15-3863-6_15
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