Short-term Load Predication Based on Wavelet Denoising Hybrid Prediction Model
Liu, Kai
Liu, Haidong
Liu, Fang
She, Yanjie
He, Xiaobo
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How to Cite

Liu K., Liu H., Liu F., She Y., He X., 2018, Short-term Load Predication Based on Wavelet Denoising Hybrid Prediction Model, Chemical Engineering Transactions, 66, 889-894.
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Abstract

This paper aims to optimize the noise attenuation effect of modern power load prediction technology. In the first place, the working principle of wavelet denoising is analyzed here. Then compare the proposed prediction model to the one built based on SARIMA and neuronal model structure, hereby we demonstrate whether this model is available. It is found by comparison that the SARIMA prediction model is prone to rendering big errors, while compared with the model based on the neuron structure, the model in this paper has a similar and higher veracity. Experimental results reveal that the denoising model proposed here has a higher accuracy and reliability.
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