Zobrazeno 1 - 10 of 107 pro vyhledávání: '"G, Rangaraj"'
1
Akademický článek
A Novel Feature Representation for Prediction of Global Horizontal Irradiance Using a Bidirectional Model
Autor: Sourav Malakar, Saptarsi Goswami, Bhaswati Ganguli, Amlan Chakrabarti, Sugata Sen Roy, K. Boopathi, A. G. Rangaraj
Publikováno v: Machine Learning and Knowledge Extraction, Vol 3, Iss 4, Pp 946-965 (2021)
Complex weather conditions—in particular clouds—leads to uncertainty in photovoltaic (PV) systems, which makes solar energy prediction very difficult. Currently, in the renewable energy domain, deep-learning-based sequence models have reported be
Externí odkaz: https://doaj.org/article/4cecab61e78a4827b7ccdcd42902c09e
Zobrazit plný text záznamu
2
Akademický článek
Impact on solar radiation parameters in India during COVID-19 lockdown: a case study
Autor: S. M. Revathy, A. G. Rangaraj, Y. Srinath, K. Boopathi, A. Shobana Devi, K. Balaraman, D. M. Reddy Prasad
Publikováno v: International Journal of Sustainable Energy, Vol 40, Iss 8, Pp 806-820 (2021)
The current research objective is to explore changes in solar radiation variables across the Indian region during the lock-down period. Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI) and Diffuse Horizontal Irradiance (DHI) were co
Externí odkaz: https://doaj.org/article/a09354c6cc6840f49f4e635ca26dc371
Zobrazit plný text záznamu
3
Akademický článek
Deep-Learning-Based Adaptive Model for Solar Forecasting Using Clustering
Autor: Sourav Malakar, Saptarsi Goswami, Bhaswati Ganguli, Amlan Chakrabarti, Sugata Sen Roy, K. Boopathi, A. G. Rangaraj
Publikováno v: Energies, Vol 15, Iss 10, p 3568 (2022)
Accurate short-term solar forecasting is challenging due to weather uncertainties associated with cloud movements. Typically, a solar station comprises a single prediction model irrespective of time and cloud condition, which often results in subopti
Externí odkaz: https://doaj.org/article/1f3092adb519407eaf7735f572eb45e0
Zobrazit plný text záznamu
4
A Novel Feature Representation for Prediction of Global Horizontal Irradiance Using a Bidirectional Model
Autor: Sugata Sen Roy, Bhaswati Ganguli, K. Boopathi, A. G. Rangaraj, Sourav Malakar, Amlan Chakrabarti, Saptarsi Goswami
Publikováno v: Machine Learning and Knowledge Extraction, Vol 3, Iss 47, Pp 946-965 (2021)
Machine Learning and Knowledge Extraction; Volume 3; Issue 4; Pages: 946-965
Complex weather conditions—in particular clouds—leads to uncertainty in photovoltaic (PV) systems, which makes solar energy prediction very difficult. Currently, in the renewable energy domain, deep-learning-based sequence models have reported be
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b92537cd75c8b5138a1c83eaac728ddc
https://www.mdpi.com/2504-4990/3/4/47
Zobrazit plný text záznamu
5
Impact on solar radiation parameters in India during COVID-19 lockdown: a case study
Autor: Y. Srinath, K. Boopathi, D.M. Reddy Prasad, K. Balaraman, S. M. Revathy, A. G. Rangaraj, A. Shobana Devi
Publikováno v: International Journal of Sustainable Energy. 40:806-820
The current research objective is to explore changes in solar radiation variables across the Indian region during the lock-down period. Global Horizontal Irradiance (GHI), Direct Normal Irradiance ...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b4456be55114d38af22c8e680031942c
https://doi.org/10.1080/14786451.2021.1893726
Zobrazit plný text záznamu
6
Hourly day-ahead wind power forecasting with the EEMD-CSO-LSTM-EFG deep learning technique
Autor: K. Boopathi, A. G. Rangaraj, A. Shobana Devi, G. Maragatham
Publikováno v: Soft Computing. 24:12391-12411
Wind power forecasting has gained significant attention due to advances in wind energy generation in power frameworks and the uncertain nature of wind. In this manner, to maintain an affordable, reliable, economical, and dependable power supply, accu
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2c33f2a5efa4d1c60c34f204bba5a776
https://doi.org/10.1007/s00500-020-04680-7
Zobrazit plný text záznamu
9
Designing a long short-term network for short-term forecasting of global horizontal irradiance
Autor: Sourav Malakar, Saptarsi Goswami, Sugata Sen Roy, K. Boopathi, A. G. Rangaraj, Bhaswati Ganguli, Amlan Chakrabarti
Publikováno v: SN Applied Sciences. 3
Long short-term memory (LSTM) models based on specialized deep neural network-based architecture have emerged as an important model for forecasting time-series. However, the literature does not provide clear guidelines for design choices, which affec
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::75a1be5fdeec644ee114cf68f26fb9b7
https://doi.org/10.1007/s42452-021-04421-x
Zobrazit plný text záznamu
10
Day-Ahead Wind Power Forecasting Using Machine Learning Algorithms
Autor: Akash. R, M. Lydia, R. Meenal, A. G. Rangaraj
Publikováno v: Computational Methods and Data Engineering ISBN: 9789811568756
As of late, natural contemplations have incited the utilization of wind power as a maintainable energy resource. Still, the biggest test in coordinating wind power into the electric grid is its irregularity. One procedure to manage wind irregularity
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e27be282e957107cd2b07d808978fbaf
https://doi.org/10.1007/978-981-15-6876-3_25
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje