基于DBSCAN算法的用电数据预处理与清洗技术研究

Research on Pre Processing and Cleaning Technology of Electricity Data Based on DBSCAN Algorithm

随着智能电网的发展,智能用电网络中的数据质量问题,如数据缺失、错误和异常,严重影响了数据分析的准确性。文章通过数据标准化、缺失值处理和DBSCAN算法等进行数据清洗,以提高数据质量,确保后续数据分析的准确性和可靠性。研究结果表明,这些技术的应用不仅提高了数据质量,还为智能电网的进一步发展提供了技术支持。

With the development of smart grids,data quality issues in smart electricity networks,such as data loss,errors,and anomalies,seriously affect the accuracy of data analysis.The article uses data standardization,missing value processing,and DBSCAN algorithm for data cleaning to improve data quality and ensure the accuracy and reliability of subsequent data analysis.The research results indicate that the application of these technologies not only improves data quality,but also provides technical support for the further development of smart grids.