Zobrazeno 1 - 6
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pro vyhledávání: '"Senthil Kumar Paramasivan"'
Autor:
Siva Sankari Subbiah, Senthil Kumar Paramasivan, Karmel Arockiasamy, Saminathan Senthivel, Muthamilselvan Thangavel
Publikováno v:
Intelligent Automation & Soft Computing. 35:3829-3844
Publikováno v:
International Journal on Recent and Innovation Trends in Computing and Communication. 10:92-105
Time series forecasting has recently emerged as a crucial study area with a wide spectrum of real-world applications. The complexity of data processing originates from the amount of data processed in the digital world. Despite a long history of succe
Autor:
Senthil Kumar Paramasivan
Publikováno v:
Revue d'Intelligence Artificielle. 35:1-10
In the modern era, deep learning is a powerful technique in the field of wind energy forecasting. The deep neural network effectively handles the seasonal variation and uncertainty characteristics of wind speed by proper structural design, objective
Autor:
Porselvi T, Senthil Kumar Paramasivan
Publikováno v:
EAI Endorsed Transactions on Energy Web, Vol 6, Iss 23 (2019)
The prediction of wind speed plays a significant role in wind energy systems. An accurate prediction of wind speed is more important for wind energy systems, but it is difficult due to its uncertain nature. This paper presents three artificial neural
Publikováno v:
Scopus-Elsevier
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::7e12344bdc8c8f6d33a525aa697761f9
http://www.scopus.com/inward/record.url?eid=2-s2.0-84904306540&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-84904306540&partnerID=MN8TOARS
Autor:
Subbiah, Siva Sankari, Paramasivan, Senthil Kumar, Arockiasamy, Karmel, Senthivel, Saminathan, Thangavel, Muthamilselvan
Publikováno v:
Intelligent Automation & Soft Computing; 2023, Vol. 35 Issue 3, p3829-3844, 16p