Следене
Santhosh Madasthu, Ph.D.
Santhosh Madasthu, Ph.D.
EPIC, University of North Carolina at Charlotte
Потвърден имейл адрес: ieee.org
Заглавие
Позовавания
Позовавания
Година
Ensemble empirical mode decomposition based adaptive wavelet neural network method for wind speed prediction
M Santhosh, C Venkaiah, DMV Kumar
Energy conversion and management 168, 482-493, 2018
2122018
Current advances and approaches in wind speed and wind power forecasting for improved renewable energy integration: A review
M Santhosh, C Venkaiah, DM Vinod Kumar
Engineering Reports 2 (6), e12178, 2020
1532020
Short-term wind speed forecasting approach using ensemble empirical mode decomposition and deep Boltzmann machine
M Santhosh, C Venkaiah, DMV Kumar
Sustainable Energy, Grids and Networks 19, 100242, 2019
972019
Short-term electric power load forecasting using random forest and gated recurrent unit
V Veeramsetty, KR Reddy, M Santhosh, A Mohnot, G Singal
Electrical Engineering 104 (1), 307-329, 2022
832022
A novel reinforced online model selection using Q-learning technique for wind speed prediction
V Kosana, K Teeparthi, S Madasthu, S Kumar
Sustainable Energy Technologies and Assessments 49, 101780, 2022
242022
A novel and hybrid framework based on generative adversarial network and temporal convolutional approach for wind speed prediction
V Kosana, K Teeparthi, S Madasthu
Sustainable Energy Technologies and Assessments 53, 102467, 2022
232022
Hybrid wind speed prediction framework using data pre-processing strategy based autoencoder network
V Kosana, K Teeparthi, S Madasthu
Electric Power Systems Research 206, 107821, 2022
202022
Hybrid convolutional Bi-LSTM autoencoder framework for short-term wind speed prediction
V Kosana, K Teeparthi, S Madasthu
Neural Computing and Applications 34 (15), 12653-12662, 2022
172022
A novel hybrid framework for wind speed forecasting using autoencoder‐based convolutional long short‐term memory network
V Kosana, S Madasthu, K Teeparthi
International Transactions on Electrical Energy Systems 31 (11), e13072, 2021
162021
Hybrid attention-based temporal convolutional bidirectional LSTM approach for wind speed interval prediction
BS Bommidi, V Kosana, K Teeparthi, S Madasthu
Environmental Science and Pollution Research 30 (14), 40018-40030, 2023
92023
A hybrid approach to ultra short-term wind speed prediction using CEEMDAN and Informer
BS Bommidi, V Kosana, K Teeparthi, S Madasthu
2022 22nd National power systems conference (npsc), 207-212, 2022
72022
Sustainable Energy, Grids and Networks Short-term wind speed forecasting approach using Ensemble Empirical Mode Decomposition and Deep Boltzmann Machine
M Santhosh, C Venkaiah
Sustainable Energy, Grids and Networks 19, 100242, 2019
62019
Meta‐heuristics algorithms for optimization of gains for dynamic voltage restorers to improve power quality and dynamics
R Veramalla, SR Arya, V Gundeboina, B Jampana, R Chilipi, S Madasthu
Optimal Control Applications and Methods, 2022
52022
Wind speed prediction using hybrid long short-term memory neural network based approach
GR Yadav, E Muneender, M Santhosh
2021 International Conference on Sustainable Energy and Future Electric …, 2021
52021
A novel dynamic selection approach using on-policy SARSA algorithm for accurate wind speed prediction
V Kosana, M Santhosh, K Teeparthi, S Kumar
Electric Power Systems Research 212, 108174, 2022
42022
Ensemble deep learning model for wind speed prediction
M Santhosh, MD Sai, S Mirza
2020 21st National Power Systems Conference (NPSC), 1-5, 2020
42020
A hybrid forecasting model based on artificial neural network and teaching learning based optimization algorithm for day-ahead wind speed prediction
M Santhosh, C Venkaiah, DMV Kumar
Intelligent Computing Techniques for Smart Energy Systems: Proceedings of …, 2020
42020
A hybrid wind speed forecasting model using complete ensemble empirical decomposition with adaptive noise and convolutional support vector machine
V Kosana, K Teeparthi, M Santhosh
2021 9th IEEE International Conference on Power Systems (ICPS), 1-6, 2021
32021
Ensemble deep learning model for power system outage prediction for resilience enhancement
S Madasthu, A Al Mamun, A Abbas, E Abbate, B Chowdhury, R Cox
2023 North American Power Symposium (NAPS), 1-6, 2023
22023
Outage Forecast-based Preventative Scheduling Model for Distribution System Resilience Enhancement
Y Yao, W Liu, R Jain, S Madasthu, B Chowdhury, R Cox
2023 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2023
22023
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