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The precision of short-term load forecasting for electric power systems directly affects the economic benefit of power systems. A hybrid method based on chaos and neural network was used in the study of the electric power system short-term load forecasting. This article presents the application of chaos method to reconstruct attractors in phase spaces and a multi-layer feed forward neural network to fit the attractor's global map, to construct a hybrid prediction model. Moreover, this article shows the efficiency of a noise-suppressing method based on single value decomposition (SVD), and a new Neural Net-work learning algorithm, chaotic learning algorithm, is proposed. The result in-dicates that the method is effective.