Open AccessA Fractional Discrete Grey Model with Particle Swarm Optimizer and Its Applications in Forecasting the Gasoline Consumption in Chongqing China
Author(s) -
Lanxi Zhang,
Yubin Cai
Publication year - 2021
Publication title -
journal of advances in mathematics and computer science
Language(s) - English
Resource type - Journals
ISSN - 2456-9968
DOI - 10.9734/jamcs/2021/v36i430356
Subject(s) - particle swarm optimization , consumption (sociology) , mathematical optimization , gasoline , nonlinear system , operator (biology) , computer science , mathematics , engineering , social science , biochemistry , chemistry , physics , repressor , quantum mechanics , sociology , transcription factor , gene , waste management
Forecasting gasoline consumption is of great significance for formulating oil production, foreign trade policies, and ensuring the balance of domestic refined oil supply. Based on grey system theory, a fractional accumulation operator is constructed to optimize the accumulation method of the traditional discrete grey model, and the Particle Swarm Optimization algorithm is used to solve the fractional nonlinear parameters. This model was used in the prediction of gasoline consumption in Chongqing, China, and compared with the existing 7 models. The results show that the fractional discrete grey model optimized by PSO has better prediction accuracy. The fractional discrete grey model optimized by PSO can be used as a quantitative method in the field of energy forecasting.