Fractional Order Grey Model of Optimization Investment Allocation for Maximum Value Addition in Beijing’s High-Tech Industries

High-tech industries are of strategic importance to the national economy, and Beijing has been designated as a science and technology innovation center by the State Council. Accurate analysis of its added value is crucial for technological development. While recent data enhance prediction accuracy, its limited volume poses challenges. The cumulative grey Lotka–Volterra model and grey differential dynamic multivariate model address this by leveraging short-term data effectively. This study applies these two models to analyze influencing factors and predict Beijing’s high-tech industry growth. Results show a competitive relationship with four systems, lacking synergy. In the next five years, a mutually beneficial trend is expected. The Mean Absolute Percentage Error (MAPE) remains within 10%, confirming the model’s reliability.

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Publication Details

Journal
Fractal and Fractional
Published
2025-04-19
DOI
https://doi.org/10.3390/fractalfract9040262
Citations
1
Primary Topic
Grey System Theory Applications
Type
article
Field-Weighted Citation Impact
2.11
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article

Fractional Order Grey Model of Optimization Investment Allocation for Maximum Value Addition in Beijing’s High-Tech Industries

Lifeng Wu, Zhenxiu Liu, Jia Li
1 citations
Fractal and Fractional
Grey System Theory Applications
2.11
article

Fractional Order Grey Model of Optimization Investment Allocation for Maximum Value Addition in Beijing’s High-Tech Industries

Lifeng Wu, Zhenxiu Liu, Jia Li
article en
1 citations

Abstract

High-tech industries are of strategic importance to the national economy, and Beijing has been designated as a science and technology innovation center by the State Council. Accurate analysis of its added value is crucial for technological development. While recent data enhance prediction accuracy, its limited volume poses challenges. The cumulative grey Lotka–Volterra model and grey differential dynamic multivariate model address this by leveraging short-term data effectively. This study applies these two models to analyze influencing factors and predict Beijing’s high-tech industry growth. Results show a competitive relationship with four systems, lacking synergy. In the next five years, a mutually beneficial trend is expected. The Mean Absolute Percentage Error (MAPE) remains within 10%, confirming the model’s reliability.

Fractal and FractionalVol. 9(4)
Hebei University of Engineering (CN), Hong Kong University of Science and Technology (HK), University of Hong Kong (HK)
Industry, innovation and infrastructure
Openalex Percentile: Top 15%
Grey System Theory Applications
2.11
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