Forecasting CO 2 emissions from road fuel combustion using grey prediction models: A novel approach.

Autor: Sapnken FE; Laboratory of Technologies and Applied Science, IUT Douala, P.O. Box 8698, Douala, Cameroon.; Transports and Applied Logistics Laboratory, University Institute of Technology, University of Douala, P.O. Box 8698, Douala, Cameroon.; Energy Insight-Tomorrow Today, PO Box 2043, Douala, Cameroon., Noume HC; Laboratory of Energy and Electrical and Electronic Systems, Department of Physics, Faculty of Science, University of Yaoundé I, P.O. Box 812, Yaoundé, Cameroon., Tamba JG; Laboratory of Technologies and Applied Science, IUT Douala, P.O. Box 8698, Douala, Cameroon.; Transports and Applied Logistics Laboratory, University Institute of Technology, University of Douala, P.O. Box 8698, Douala, Cameroon.; Energy Insight-Tomorrow Today, PO Box 2043, Douala, Cameroon.
Jazyk: angličtina
Zdroj: MethodsX [MethodsX] 2023 Jun 28; Vol. 11, pp. 102271. Date of Electronic Publication: 2023 Jun 28 (Print Publication: 2023).
DOI: 10.1016/j.mex.2023.102271
Abstrakt: This paper proposes an optimized wavelet transform Hausdorff multivariate grey model (OWTHGM(1,N)) that addresses some of the weaknesses of the conventional GM(1,N) model such as inaccurate prediction and poor stability. Three improvements have been made: First, all inputs are filtered using a wavelet transform; second, a new time response function is established using the Hausdorff derivative; and finally, the use of Rao's algorithm to optimise the model's parameters as well as the ξ -order accumulated value of the observation data described by the Hausdorff derivative. In order to demonstrate the effectiveness of OWTHGM(1,N), it is applied to predict CO 2 emissions from road fuel combustion. The new model scores 1.27% MAPE and 79.983 RMSE, and is therefore more accurate than competing models. OWTHGM(1,N) could therefore serve a reliable forecasting tool and used to monitor the evolution of CO 2 emissions in Cameroon. The forecast results also serve as a sound foundation for the formulation of energy consumption strategies and environmental policies. • Modification, extension and optimization of grey multivariate model is done. • The model is very generic can be applied to a wide variety of energy sectors. • OWTHGM(1,N) is a valid forecasting tool that can be used to track CO 2 emissions.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2023 The Author(s).)
Databáze: MEDLINE
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