a novel multiscale ensemble carbon price prediction model integrating empirical mode decomposition, genetic algorithm and artificial neural network一种新的多尺度合奏碳价格预测模型集成经验模态分解,遗传算法和人工神经网络.pdfVIP

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a novel multiscale ensemble carbon price prediction model integrating empirical mode decomposition, genetic algorithm and artificial neural network一种新的多尺度合奏碳价格预测模型集成经验模态分解,遗传算法和人工神经网络.pdf

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a novel multiscale ensemble carbon price prediction model integrating empirical mode decomposition, genetic algorithm and artificial neural network一种新的多尺度合奏碳价格预测模型集成经验模态分解,遗传算法和人工神经网络

Energies 2012, 5, 355-370; doi:10.3390/en5020355 OPEN ACCESS energies ISSN 1996-1073 /journal/energies Article A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network Bangzhu Zhu School of Economics and Management, Wuyi University, Jiangmen 529020, Guangdong, China; E-Mail: wpzbz@126.com; Tel.: +86-0750-3296568; Fax: +86-0750-3299335 Received: 8 December 2011; in revised form: 8 February 2012 / Accepted: 8 February 2012 / Published: 17 February 2012 Abstract: Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble forecasting model integrating empirical mode decomposition (EMD), genetic algorithm (GA) and artificial neural network (ANN) is proposed to forecast carbon price. Firstly, the proposed model uses EMD to decompose carbon price data into several intrinsic mode functions (IMFs) and one residue. Then, the IMFs and residue are composed into a high frequency component, a low frequency component and a trend component which have similar frequency characteristics, simple components and strong regularity using the fine-to-coarse reconstruction algorithm. Finally, those three components