Ramadhan Short-Term Electric Load: A Hybrid Model of Cycle Spinning Wavelet and Group Method Data Handling (CSW-GMDH)
In general, performing a nonlinearity time series analysis in the modeling of data can reach a robust and increase the quality of the results. Wavelet methods have successfully been applied in a great variety of applications for modeling also forecasting. Wavelet Transform divided into two categories. There is continuous wavelet (CWT) and a discrete wavelet transform (DWT). Cycle spinning unlike the discrete wavelet transform (DWT), is highly redundant, non-orthogonal, also defined naturally for all sample sizes. There is a Group Method of Data Handling (GMDH) algorithm, which is a multivariate analysis method can be used in modeling and identifying uncertainty on linear also nonlinearity systems. In this paper, we aim to explain the combination of À-Trous wavelet transforms applied on cycle spinning and group method of data handling (GMDH) in data of short-term electric load holy month of Ramadhan from 2014 to 2015.
IAENG International Journal of Computer Science Vol. 46, No. 4, 2019
Rezzy Eko Caraka, Rung Ching Chen, Toni Toharudin, Bens Pardamean, Sakhinah Abu Bakar, Hasbi Yasin
