基于多数据源的水利数据采集与大数据服务

Xu Zhu
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引用次数: 0

摘要

为体现数据开发的应用价值,以多数据源数据为基础,对水利和大数据服务进行了研究。首先,对公共数据的获取进行了研究。利用计算机快速高效地将数据录入图书馆,大大降低了数据采集的难度。然后确定数据清洗的方法,以提高数据质量,增强数据在应用过程中的有效性和可靠性。最后,将该水利预测模型应用于基于综合平台的防洪决策服务系统。结果表明,公共数据的采集大大提高了数据采集的效率。通过对所得数据的重复值、误差值、离群值和缺失值进行清洗,得到质量较高的水情数据。水利预测模型提高了预测精度,防洪决策服务系统提供了一个高效、可操作的综合平台。因此,水利预测模型对防洪决策具有一定的指导作用。是水利大数据服务的关键。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Water Conservancy Data Acquisition and Big Data Service Based on Multi-data Sources
To reflect the application value of data development, based on the data of multiple data sources, the water conservancy and the big data service were studied. First, the acquisition of public data was studied. Computers were used to quickly and efficiently collect data into libraries, which greatly reduce the difficulty of data acquisition. Then, the method of data cleaning was determined to improve data quality and enhance the effectiveness and reliability of the data in the application process. Finally, the water conservancy prediction model was applied to the flood prevention decision-making service system based on the integrated platform. The results showed that the acquisition of public data greatly improved the efficiency of data acquisition. By cleaning the obtained data of repeated values, error values, outliers and missing values, higher quality water situation data was obtained. The water conservancy prediction model improved the accuracy of the prediction, and the flood control decision service system provided an efficient and operational integrated platform. Therefore, the water conservancy prediction model has a certain guiding role in flood control decision-making. It is the key to big data services for water conservancy.
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