In this paper, we synthetically applied genetic algorithm (GA) and artificial neural network (ANN) technology to automatically diagnose the fault of power transformer. The optimization based on the genetic algorithm is executed on the neural network thresholds and weights values. The test results show that the optimized BP network by genetic algorithm has an excellent performance on training speed and diagnosis reliability, and its prediction accuracy outperforms traditional BP in fault diagnosis of power transformer. © Springer-Verlag Berlin Heidelberg 2011.
CITATION STYLE
Zhao, W., Kang, Y., Pan, G., & Huang, X. (2011). Fault Diagnosis of Power Transformer Based on BP Combined with Genetic Algorithm. In Communications in Computer and Information Science (Vol. 134, pp. 33–38). https://doi.org/10.1007/978-3-642-18129-0_6
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