Red deer optimized recurrent neural network for the classification of power quality disturbance-Reference-Cited by-同舟云学术

Red deer optimized recurrent neural network for the classification of power quality disturbance

Published:2023-01-04 Issue:4 Volume:105 Page:1937-1953
ISSN:0948-7921
Container-title:Electrical Engineering
language:en
Short-container-title:Electr Eng

Author:

Dawood Zamrooth,Babulal C. K.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Electrical and Electronic Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00202-022-01701-6.pdf

Reference35 articles.

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2. Kiruthiga B, Banu RN, Devaraj D (2020) Detection and classification of power quality disturbances or events by adaptive NFS classifier. Soft Comput 24(14):10351–10362

3. Chawda GS, Shaik AG, Shaik M, Padmanaban S, Holm-Nielsen JB, Mahela OP, Kaliannan P (2020) Comprehensive review on detection and classification of power quality disturbances in utility grid with renewable energy penetration. IEEE Access 8:146807–146830

4. Cortes-Robles O, Barocio E, Obushevs A, Korba P, Sevilla FRS (2021) Fast-training feedforward neural network for multi-scale power quality monitoring in power systems with distributed generation sources. Measurement 170:108690

5. Ray P, Budumuru GK, Mohanty BK (2018) A comprehensive review on soft computing and signal processing techniques in feature extraction and classification of power quality problems. J Renew Susta Energy 10(2):025102

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