Title :
Spectral mixture kernel for pattern discovery and time series forecasting of electricity peak load
Author :
Ploysuwan, Tuchsanai
Author_Institution :
Dept. of Electr. Eng., Siam Univ. Bangkok, Bangkok, Thailand
Abstract :
In this paper, the author presents the joint of spectral mixture Gaussian and a single squared exponential kernel function which used in predictive solution of Gaussian process (GP) to find new pattern discovery and forecasting of electricity peak load demand of Thailand in next five years. Several analytical results have been evaluated in simulations such as pattern discovery performance, property of each kernel function, and mean absolute percentage error (MAPE) of the method.
Keywords :
Gaussian processes; load forecasting; mixture models; time series; GP; Gaussian process; MAPE; as pattern discovery performance; electricity peak load; mean absolute percentage error; single squared exponential kernel function; spectral mixture Gaussian; spectral mixture kernel; time series forecasting; Decision support systems; Financial management; Hafnium; Planning; Gaussian process; Peak load forecasting; Spectral mixture Gaussian kernel;
Conference_Titel :
TENCON 2014 - 2014 IEEE Region 10 Conference
Conference_Location :
Bangkok
Print_ISBN :
978-1-4799-4076-9
DOI :
10.1109/TENCON.2014.7022373