Cite
Initial condition based real time classification of power quality disturbance using deep convolution neural network with bidirectional long short‐term memory.
MLA
Kandasamy, Prabaakaran, et al. “Initial Condition Based Real Time Classification of Power Quality Disturbance Using Deep Convolution Neural Network with Bidirectional Long Short‐term Memory.” IET Generation, Transmission & Distribution (Wiley-Blackwell), vol. 17, no. 23, Dec. 2023, pp. 5135–54. EBSCOhost, https://doi.org/10.1049/gtd2.13026.
APA
Kandasamy, P., Kumar, C., Lakshmanan, M., Jaisiva, S., Stonier, A. A., Peter, G., & Ganji, V. (2023). Initial condition based real time classification of power quality disturbance using deep convolution neural network with bidirectional long short‐term memory. IET Generation, Transmission & Distribution (Wiley-Blackwell), 17(23), 5135–5154. https://doi.org/10.1049/gtd2.13026
Chicago
Kandasamy, Prabaakaran, Chandrasekaran Kumar, Muthuramalingam Lakshmanan, Selvaraj Jaisiva, Albert Alexander Stonier, Geno Peter, and Vivekananda Ganji. 2023. “Initial Condition Based Real Time Classification of Power Quality Disturbance Using Deep Convolution Neural Network with Bidirectional Long Short‐term Memory.” IET Generation, Transmission & Distribution (Wiley-Blackwell) 17 (23): 5135–54. doi:10.1049/gtd2.13026.