Showing papers by "Zhao Yang Dong published in 2001"
TL;DR: In this article, the authors proposed a model for short term load forecast in the competitive electricity market based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons or MLPs) modeling of wavelet coefficients.
179 citations
01 Jan 2001
TL;DR: In this paper, a time series load forecast model based on wavelet multi-resolution decomposition and the neural network modeling of wavelet coefficients is proposed for the Australian National Electricity Market.
Abstract: This paper proposes a time series load forecast model suited to competitive electricity markets. The forecast model is based on wavelet multi-resolution decomposition and the neural network modeling of wavelet coefficients. A Bayesian method automatic relevance determination (ARD) model is used to choose the optimal neural network size. The individual wavelet domain neural network forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market.
19 citations
Proceedings Article•
01 Jan 2001
2 citations
Proceedings Article•
01 Jan 2001
1 citations
TL;DR: The existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given, and the minimum- order stable linear predictor is obtained via solving an optimization problem.
Abstract: In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.