Industrialization and innovation strategy of event resources in ice and snow sports under the background of big data

Abstract

This article examines the industrialization and innovative strategy of event resources in ice and snow sports in the context of big data. Based on this analysis, the article proposes a path and development strategy for the Chinese sports industry, which includes encouraging the industrialization of the nation’s ice and snow sports industry. It is important to evaluate ice and snow sports in order to improve competitive results and optimize training techniques using big data technologies. Despite using a variety of techniques to evaluate performance, their inability to fully capture the complex patterns found in ice and snow sports events presents difficulties. In order to assess and enhance sports talents, therefore we proposed a new method using ISSE-Apriori algorithms. The pre-processed data gathered before extracting the most important and relevant features. The experiment results section analyzes the resources of ice and snow sports cities. The results examine sports event strategies, taking into account predictions and actual accuracy results, the GDP growth rate, the efficiency of industrial development, and a comparison of Apriori before and after enhancement. The experimental result is validating using measures like recall, accuracy, and precision. In addition, we conducted a comparative analysis with the current approaches to confirm the efficiency and robustness of the proposed methodology. The Suggested approach is implemented with Python Software. The Suggested Approach’s performance is measured in terms of RMSE (0.3524), MAE (0.1832), MAPE (4.24) with large dataset. The results stated that the proposed methodology has provided an accuracy of 98.42%.