A study on forecasting the popularity of Chinese national brands using a grey-weighted Markov model

Based on the foundation of grey system theory, this study enhances and improves the GM(1,1) prediction model by proposing a grey-weighted Markov model prediction method. This method is employed to construct a brand popularity prediction model, aiming to optimize the model and enhance the accuracy of brand popularity forecasts. The research findings indicate that compared to the singular GM(1,1) prediction model, the grey-weighted Markov model significantly increases the precision in predicting brand popularity. Furthermore, the constructed grey-weighted Markov model demonstrates minor fluctuations in absolute error, indicating model stability. This provides a simple yet accurate forecasting method for the prediction of Chinese national brand popularity.