Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Chetan B. Khadse"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-23 (2024)
Abstract The growing integration of renewable energy sources into grid-connected microgrids has created new challenges in power generation forecasting and energy management. This paper explores the use of advanced machine learning algorithms, specifi
Externí odkaz:
https://doaj.org/article/c362974d477441a9ac7db9ce8e32990d
Autor:
Abhay Kumar, Rupesh Kumar Jha, Manuele Bertoluzzo, Chetan B. Khadse, Swati Jaiswal, Gourang Mulay, Amritansh Sagar
Publikováno v:
Designs, Vol 7, Iss 4, p 92 (2023)
Two different arrangements for Wireless Battery Charging Systems (WBCSs) with a series-parallel resonant topology have been analyzed in this paper. The first arrangement charges the battery by controlling the receiver-side rectifier current and volta
Externí odkaz:
https://doaj.org/article/f5149b0cb57a465ea347a62014cfd85b
Publikováno v:
Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. :1-15
An electromagnetic field and artificial intelligence-based transmission line protection system for smart grid is proposed in this paper. Bayesian regularization neural network is used as an intelli...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::edbd05e0d40d512d105b2d84fd71933a
https://doi.org/10.1080/15567036.2021.1948637
https://doi.org/10.1080/15567036.2021.1948637
Publikováno v:
Smart Technologies for Energy, Environment and Sustainable Development, Vol 1 ISBN: 9789811668746
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b975919238aea31215c478582d269e80
https://doi.org/10.1007/978-981-16-6875-3_48
https://doi.org/10.1007/978-981-16-6875-3_48
Publikováno v:
Springer Proceedings in Energy ISBN: 9789811668784
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5568c187d7b1f3b29e18096b1bd6a01
https://doi.org/10.1007/978-981-16-6879-1_61
https://doi.org/10.1007/978-981-16-6879-1_61
Publikováno v:
2021 6th International Conference for Convergence in Technology (I2CT).
An artificial neural network based three phase real time power quality analysis is proposed in this paper. The scaled conjugate gradient descent algorithm is used as a learning algorithm for neural network. The training and testing data required is g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07963a33da61e9f805b1b398a9f12d7e
https://doi.org/10.1109/i2ct51068.2021.9418004
https://doi.org/10.1109/i2ct51068.2021.9418004
This book provides a comprehensive review of the latest developments in optimization based learning algorithms within the field of electrical engineering. It covers various power system applications including efficient power system operation, load fo
Publikováno v:
2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT).
In this paper, artificial neural network model developed for the prediction of PM2.5 particulate matter is discussed. Along with artificial neural network, multiple linear regression model is developed for the prediction. Both the techniques are comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13632d53e1d63445b75e84fc2965f871
https://doi.org/10.1109/icaect49130.2021.9392611
https://doi.org/10.1109/icaect49130.2021.9392611
Publikováno v:
2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT).
In this paper, a fault identification system based on the artificial neural network is proposed. An 11 KV transmission line model is developed in MATLAB simulink model. The faults under considerations are line to ground, line to line, double line to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64ed35975e98801f95ae58e7b697a8dc
https://doi.org/10.1109/icaect49130.2021.9392433
https://doi.org/10.1109/icaect49130.2021.9392433
Publikováno v:
IEEE Transactions on Industrial Informatics. 13:1036-1045
In this paper, an electromagnetic compatibility estimator is proposed using an artificial neural network with a scaled conjugate gradient algorithm. Neural networks are trained with the help of seven different optimization algorithms in MATLAB. Their
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14b40e2ece9f6ad5e54822f889201e41
https://doi.org/10.1109/tii.2016.2605623
https://doi.org/10.1109/tii.2016.2605623