Carbon Dioxide Emission Forecasting Using BiLSTM Network Based on Variational Mode Decomposition and Improved Black-Winged Kite Algorithm

Yueqiao Yang, Shichuang Li (), Haijun Liu and Jidong Guo
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Yueqiao Yang: School of Emergency Management, Institute of Disaster Prevention, Langfang 065201, China
Shichuang Li: School of Information Management, Institute of Disaster Prevention, Langfang 065201, China
Haijun Liu: School of Emergency Management, Institute of Disaster Prevention, Langfang 065201, China
Jidong Guo: School of Emergency Management, Institute of Disaster Prevention, Langfang 065201, China

Mathematics, 2025, vol. 13, issue 11, 1-30

Abstract: With the growing severity of global climate change, forecasting and managing carbon dioxide (CO 2 ) emissions has become one of the critical tasks in addressing climate change. To improve the accuracy of CO 2 emission forecasting, an innovative framework based on variational mode decomposition (VMD), improved black-winged kite algorithm (IBKA), and BiLSTM networks is proposed. This framework aims to address the challenges associated with predicting non-stationary data and optimizing model hyperparameters. Initially, experiments were conducted on 29 benchmark functions using the IBKA algorithm, demonstrating its superior performance in highly nonlinear and complex environments. Subsequently, the BiLSTM model optimized by IBKA was employed to predict CO 2 emission trends across four major industries in China, confirming its enhanced prediction accuracy. Finally, a comparative analysis with other mainstream machine learning and deep learning models revealed that the BiLSTM model consistently achieved the best predictive performance across all industries. This research proposes an efficient and practical technical pathway for intelligent carbon emission prediction under the “dual-carbon” strategic goals, offering scientific support for policy formulation and the low-carbon transition.

Keywords: improved black-winged kite algorithm; carbon dioxide emission forecasting; variational mode decomposition; hyperparameter optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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