Huizhou GDP forecast based on fractional opposite-direction accumulating nonlinear grey bernoulli markov model

Meilan Qiu; Dewang Li; Zhongliang Luo; Xijun Yu; Meilan Qiu; Dewang Li; Zhongliang Luo; Xijun Yu

doi:10.3934/era.2023047

Electronic Research Archive

2023, Volume 31, Issue 2: 947-960. doi: 10.3934/era.2023047

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Huizhou GDP forecast based on fractional opposite-direction accumulating nonlinear grey bernoulli markov model

1.
Division of Applied and Computational Mathematics, Beijing Computational Science Research Center, Beijing 100193, China
2.
School of Mathematics and Statistics, Huizhou University, Guangdong, Huizhou 516007, China
3.
School of Electronic and Information Engineering, Huizhou University, Guangdong, Huizhou 516007, China
4.
Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Beijing 100088, China

Received: 04 October 2022 Revised: 22 November 2022 Accepted: 23 November 2022 Published: 06 December 2022

In this paper, a fractional opposite-direction accumulating nonlinear grey Bernoulli Markov model (FOANGBMKM) is established to forecast the annual GDP of Huizhou city from 2017 to 2021. The optimal fractional order number and nonlinear parameters of the model are determined by particle swarm optimization (PSO) algorithm. An experiment is provided to validate the high fitting accuracy of this model, and the effect of prediction is better than that of the other four competitive models such as autoregressive integrated moving average model (ARIMA), grey model (GM (1, 1)), fractional accumulating nonlinear grey Bernoulli model (FANGBM (1, 1)) and fractional opposite-direction accumulating nonlinear grey Bernoulli model (FOANGBM (1, 1)), which proves the robustness of the opposite-direction accumulating nonlinear Bernoulli Markov model. This research will provide a scientific basis and technical references for the economic planning industries.
- FOANGBMKM (1, 1),
- GDP,
- PSO algorithm,
- differential equation,
- forecast
Citation: Meilan Qiu, Dewang Li, Zhongliang Luo, Xijun Yu. Huizhou GDP forecast based on fractional opposite-direction accumulating nonlinear grey bernoulli markov model[J]. Electronic Research Archive, 2023, 31(2): 947-960. doi: 10.3934/era.2023047

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Abstract

In this paper, a fractional opposite-direction accumulating nonlinear grey Bernoulli Markov model (FOANGBMKM) is established to forecast the annual GDP of Huizhou city from 2017 to 2021. The optimal fractional order number and nonlinear parameters of the model are determined by particle swarm optimization (PSO) algorithm. An experiment is provided to validate the high fitting accuracy of this model, and the effect of prediction is better than that of the other four competitive models such as autoregressive integrated moving average model (ARIMA), grey model (GM (1, 1)), fractional accumulating nonlinear grey Bernoulli model (FANGBM (1, 1)) and fractional opposite-direction accumulating nonlinear grey Bernoulli model (FOANGBM (1, 1)), which proves the robustness of the opposite-direction accumulating nonlinear Bernoulli Markov model. This research will provide a scientific basis and technical references for the economic planning industries.

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