Research on the Evaluation of Predictive Power Data Service Based on Improved Entropy Weight and Cloud Model

Predictive power data services are an effective way to unleash the value of power data. In response to the current lack of effective evaluation for such services, this paper proposes an evaluation system and method for assessing the quality of predictive power data services. The objective is to enhance service quality, improve service benefits, and provide better decision support and management tools for the power industry. The proposed approach is based on the cloud model principle. The golden section method is employed to generate the cloud, while the improved entropy weight method is used to calculate the weights. The effectiveness of the proposed evaluation method is validated through the evaluation of predictive power data services provided in different regions.