A novel fractional time-delayed grey model with discrete fractal derivative and its applications in predicting enrollments and educational expenditure

Xie, Wanli; Liu, Caixia

doi:10.1007/s00500-023-09158-w

Soft Comput

2023

DOI: 10.1007/s00500-023-09158-w

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A novel fractional time-delayed grey model with discrete fractal derivative and its applications in predicting enrollments and educational expenditure

Wanli Xie,

Caixia Liu

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Cited by 3 publications

References 31 publications

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A novel fractional neural grey system model with discrete q-derivative

Xu,

Liu,

Liang

2024

Complex Intell. Syst.

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The challenge of predicting time series with limited data has evolved over time due to nonlinearity, complexity, and limited information. It can be perceived as a mapping of dynamical systems in one-dimensional space. This article proposes a neural grey system to tackle this challenge. The system enhances its ability to fit nonlinearity by employing polynomials, captures complexity through a fractional-order cumulant operator, and resolves information-poor uncertainty by utilizing grey system modeling techniques. The model effectively integrates research findings from neural computing, uncertainty theory, and complexity theory at a theoretical level. It accurately describes dynamic processes of complex systems. Additionally, we have reduced the complexity of calculations in the algorithm design. We selected a dataset of total retail sales of consumer goods to test the model’s validity and applicability. Our experiments demonstrate that the newly proposed grey forecasting model can effectively forecast time series with small samples, offering good forecasting outcomes and generalization ability.

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A novel fractional neural grey system model with discrete q-derivative

Xu,

Liu,

Liang

2024

Complex Intell. Syst.

View full text Add to dashboard Cite

show abstract

Roughness prediction of asphalt pavement using FGM(1,1—sin) model optimized by swarm intelligence and Markov chain

Li,

Cao,

Shi

et al. 2025

Neural Networks

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A novel multi-scale fractional-order Bernoulli grey model and its application on primary school scale prediction

Liu,

Zhao,

2024

Communications in Statistics - Simulation and Computation

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A novel fractional time-delayed grey model with discrete fractal derivative and its applications in predicting enrollments and educational expenditure

Cited by 3 publications

References 31 publications

A novel fractional neural grey system model with discrete q-derivative

A novel fractional neural grey system model with discrete q-derivative

Roughness prediction of asphalt pavement using FGM(1,1—sin) model optimized by swarm intelligence and Markov chain

A novel multi-scale fractional-order Bernoulli grey model and its application on primary school scale prediction

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