Hybridization of ensemble Kalman filter and non-linear auto-regressive neural network for financial forecasting
S Jadid Abdulkadir, SP Yong, M Marimuthu… - Mining Intelligence and …, 2014 - Springer
Financial data is characterized as non-linear, chaotic in nature and volatile thus making the
process of forecasting cumbersome. Therefore, a successful forecasting model must be able …
process of forecasting cumbersome. Therefore, a successful forecasting model must be able …
Load forecasting with support vector machines and semi-parametric method
JA Jordaan, A Ukil - … Conference on Intelligent Data Engineering and …, 2007 - Springer
A new approach to short-term electrical load forecasting is investigated in this paper. As
electrical load data are highly non-linear in nature, in the proposed approach, we first …
electrical load data are highly non-linear in nature, in the proposed approach, we first …
Short term load forecasting using semi-parametric method and support vector machines
JA Jordaan, A Ukil - AFRICON 2009, 2009 - ieeexplore.ieee.org
Accurate short term load forecasting plays a very important role in power system
management. As electrical load data is highly non-linear in nature, in the proposed …
management. As electrical load data is highly non-linear in nature, in the proposed …
Short term load forecasting using non-linear template matching
JA Jordaan, A Ukil - IEEE Africon'11, 2011 - ieeexplore.ieee.org
Accurate short term load forecasting plays a very important role in power system
management. As electrical load data is highly non-linear in nature, in the proposed …
management. As electrical load data is highly non-linear in nature, in the proposed …