 Fractal derivative fractional grey Riccati model and its applicationYonghong Zhang, Shuhua Mao, Yuxiao Kang and Jianghui Wen Chaos, Solitons & Fractals, 2021, vol. 145, issue C Abstract: Fractal geometry methods are widely used to describe the geometric characteristics of complex systems, statistical behaviors, and power-law characteristics of data results. In this study, the fractal derivative and fractional cumulative generating operators are introduced into the grey Riccati model to establish the fractal derivative and fractional grey Riccati model (FDFGRM), and the analytical solution of the model is obtained. At the same time, multi-objective quantum particle swarm optimization algorithm is used for parameter optimization. We consider China's cement production, natural gas production, and primary aluminum production as examples to verify the validity of the model. The results show that the fitting and testing effects of the FDFGRM are better than those of other models. Finally, FDFGRM is used to predict the future trends of these three cases. Keywords: Fractal derivative; Fractional accumulation generation; Grey Riccati model; Multi-objective optimization (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:145:y:2021:i:c:s0960077921001302 DOI: 10.1016/j.chaos.2021.110778 Access Statistics for this article Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros More articles in Chaos, Solitons & Fractals from Elsevier |
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