Grey Holt-Winters Model and Grey Wolf Optimization for the Egg Price Forecasting in China

2025-09-22T07:16:15+00:00

To deal with the egg price forecasting in China, the grey Holt-Winters model is optimized by the Grey Wolf Algorithm. The optimized grey Holt-Winters model outperform support vector regression for forecasting the price of eggs in the four provinces of China. The seasonality of egg price is also discussed in the current study. The forecast accuracy is gauged through the Mean Absolute Percent Error and the Root Mean Square Error. The proposed model's forecasts will provide the egg producers and consumers with better long-term information.

Forecasting Global Digital Infrastructure Capacity with an Optimized Discrete Grey Model

2025-12-22T12:38:56+00:00

The rapid expansion of digital infrastructure presents significant forecasting and strategic planning challenges for investors and corporate decision-makers. This study applies the DGM (1,1,α) grey forecasting model to project the growth of four critical variables to 2030: global network traffic, data creation, data centre supply, and data centre demand, using secondary data. The model demonstrates high in-sample accuracy, with Mean Absolute Percentage Errors (MAPE) below 1.35%. A comparative analysis with industry benchmarks reveals strong alignment, validating the model's robustness. Key findings project sustained near-exponential growth and a critical narrowing of the global supply-demand margin. The results highlight impending market tightness and provide a quantitative framework for strategic capacity planning, capital allocation, and risk mitigation in the digital infrastructure sector, directly supporting data-driven management science applications.

International Journal of Grey Systems

Grey Holt-Winters Model and Grey Wolf Optimization for the Egg Price Forecasting in China

Forecasting Global Digital Infrastructure Capacity with an Optimized Discrete Grey Model