Dynamic Evaluation of Intelligent Index Systems: Incorporating Vertical and Horizontal Grading Method

In the context of benchmark regression, the entropy method is utilized to ascertain the intelligent index system. This particular method facilitates an objective weighting of each index by calculating the dispersion degree between data, thereby retaining the original data sample information to the greatest extent possible. It is a popular approach to address evaluation models involving data. However, its suitability is limited to panel data at a single time point, while its application to time series panel data lacks explanatory power. Consequently, to avoid calculation deviation caused by the static evaluation method, the vertical and horizontal grading method is employed to evaluate the index system. This method maximizes the differences between evaluation objects in the time series three-dimensional data table, enabling dynamic comparability of the evaluation results. Please refer to the appendix for a detailed outline of the vertical and horizontal grading method.