Abstract: At present, the cloud service platform for safety monitoring of small and medium-sized reservoirs in Xinjiang has been built, and the monitoring data from various regions have been collected to the cloud platform, which has gradually resulted in a large amount of safety monitoring data and has the basic characteristics of big data. With the rapid development of the Internet of Things, artificial intelligence, machine learning algorithms and other technologies, smart reservoirs have gradually become the development goal under the current situation. This paper mainly introduces how the data analysis model based on big data theory is applied to the safety monitoring platform of small and medium-sized reservoirs in Xinjiang, and the results show that the data analysis model based on big data theory has a good application result, which verifies the usability of big data theory in safety monitoring and the reliability of big data analysis model, as well as provides reference for monitoring data analysis of small and medium-sized reservoirs.

Key words: big data, data analysis models, cloud platform, machine learning algorithms

摘要： 目前新疆中小型水库安全监测云服务平台已搭建完毕，各地区监测数据汇聚到云平台，逐渐积累了大量安全监测数据，具备了大数据的基本特征。随着物联网、人工智能和机器学习算法等技术的高速发展，智慧水库逐渐成为当下的发展目标。笔者主要介绍基于大数据理论的数据分析模型在新疆中小型水库安全监测平台中的应用，实例结果表明依据大数据理论的数据分析模型应用效果良好，验证了大数据理论在安全监测中的可用性及大数据分析模型的可靠性，为中小型水库安全监测数据分析提供参考。

关键词: 大数据, 数据分析模型, 云平台, 机器学习算法