Predicting regional carbon price in China based on multi-factor HKELM by combining secondary decomposition and ensemble learning
Beibei Hu,
Yunhe Cheng
Abstract:Accurately predicting carbon price is crucial for risk avoidance in the carbon financial market. In light of the complex characteristics of the regional carbon price in China, this paper proposes a model to forecast carbon price based on the multi-factor hybrid kernel-based extreme learning machine (HKELM) by combining secondary decomposition and ensemble learning. Variational mode decomposition (VMD) is first used to decompose the carbon price into several modes, and range entropy is then used to reconstruct … Show more
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