Zobrazeno 1 - 10
of 345
pro vyhledávání: '"R, Sunitha"'
Publikováno v:
In International Journal of Electrical Power and Energy Systems July 2024 158
Publikováno v:
In Procedia Computer Science 2024 235:745-756
Publikováno v:
In Energy & Buildings 1 November 2023 298
Autor:
Syam Mohan E, R. Sunitha
Publikováno v:
Data in Brief, Vol 50, Iss , Pp 109452- (2023)
Regional languages are being used more frequently in online platforms as a result of the expanding use of digital technology. Understanding user opinions on social media platforms, forums, blogs, and other digital platforms that employ Indian regiona
Externí odkaz:
https://doaj.org/article/15d54600570b4a70ad8b48ebe2bb99a5
Autor:
Arun Kumar, R. Sunitha
Publikováno v:
Intelligent Systems with Applications, Vol 18, Iss , Pp 200227- (2023)
A typical application of spatio-temporal data is traffic flow prediction. Precise traffic prediction needs to exploit the latent spatial, temporal and spatio-temporal dependencies. Most of the recent works on traffic prediction, based on deep learnin
Externí odkaz:
https://doaj.org/article/23e6739466f34357b9cc626363043098
Publikováno v:
Journal of Natural Fibers, Vol 20, Iss 1 (2023)
As a futuristic approach an attempt has been made in this study to improve the compatibility between reinforcement and polymer matrix in composites by various chemical treatments. The adhesion of these can be achieved by modifying the surface using t
Externí odkaz:
https://doaj.org/article/6f3ac730d29b41f8b2ee3158007c0e82
Autor:
Kannan T, Gokul, M, Maheswari, K, Suganya, K, Bhuvaneswari, Kannan, Balaji, R, Sunitha, S, Manikandan.
Publikováno v:
International Journal of Environmental Analytical Chemistry; Dec2024, Vol. 104 Issue 17, p5574-5591, 18p
Autor:
R., Sunitha
Publikováno v:
Journal on Innovations in Teaching & Learning; Jun2024, Vol. 3 Issue 2, p1-12, 12p
Autor:
G. S. Thejas, Rameshwar Garg, S. S. Iyengar, N. R. Sunitha, Prajwal Badrinath, Shasank Chennupati
Publikováno v:
IEEE Access, Vol 9, Pp 128687-128701 (2021)
Feature selection has emerged as a craft, using which we boost the performance of our learning model. Feature or Attribute Selection is a data preprocessing technique, where only the most informative features are considered and given to the predictor
Externí odkaz:
https://doaj.org/article/1628312443244aec8c20351d0e866fe0