Parul Arora,Himanshu Kumar,Bijaya Ketan Panigrahi

With the advent of huge data availability and cheap processing power to derive insights from data ,applications of Big Data and Machine Learning are gaining popularity in every industry. Now, Predicting about future is no more an alternate but a necessity to increase efficiency with accurate output. Forecasting for a shorter duration (Nowcasting) fits perfectly in this space to estimate the final production for better planning and control.

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Parul Arora,Himanshu Kumar,Bijaya Ketan Panigrahi [1] Parul Arora,Himanshu Kumar,Bijaya Ketan Panigrahi, "Time Series Nowcasting of Wind Speed using Tree based Ensemble Methods", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/wjak-kv58. Accessed: Sep. 18, 2020.
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doi = {10.21227/wjak-kv58},
url = {http://dx.doi.org/10.21227/wjak-kv58},
author = {Parul Arora;Himanshu Kumar;Bijaya Ketan Panigrahi },
publisher = {IEEE Dataport},
title = {Time Series Nowcasting of Wind Speed using Tree based Ensemble Methods},
year = {2018} }
TY - DATA
T1 - Time Series Nowcasting of Wind Speed using Tree based Ensemble Methods
AU - Parul Arora;Himanshu Kumar;Bijaya Ketan Panigrahi
PY - 2018
PB - IEEE Dataport
UR - 10.21227/wjak-kv58
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Parul Arora,Himanshu Kumar,Bijaya Ketan Panigrahi. (2018). Time Series Nowcasting of Wind Speed using Tree based Ensemble Methods. IEEE Dataport. http://dx.doi.org/10.21227/wjak-kv58
Parul Arora,Himanshu Kumar,Bijaya Ketan Panigrahi, 2018. Time Series Nowcasting of Wind Speed using Tree based Ensemble Methods. Available at: http://dx.doi.org/10.21227/wjak-kv58.
Parul Arora,Himanshu Kumar,Bijaya Ketan Panigrahi. (2018). "Time Series Nowcasting of Wind Speed using Tree based Ensemble Methods." Web.
1. Parul Arora,Himanshu Kumar,Bijaya Ketan Panigrahi. Time Series Nowcasting of Wind Speed using Tree based Ensemble Methods [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/wjak-kv58
Parul Arora,Himanshu Kumar,Bijaya Ketan Panigrahi. "Time Series Nowcasting of Wind Speed using Tree based Ensemble Methods." doi: 10.21227/wjak-kv58