Junde Chen1, Jiajia Yuan2, Weirong Chen3, Adnan Zeb4, Md Suzauddola5, Yaser A. Nanehkaran2,*
CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2575-2591, 2024, DOI:10.32604/cmc.2024.048522
- 27 February 2024
Abstract Missing value is one of the main factors that cause dirty data. Without high-quality data, there will be no reliable analysis results and precise decision-making. Therefore, the data warehouse needs to integrate high-quality data consistently. In the power system, the electricity consumption data of some large users cannot be normally collected resulting in missing data, which affects the calculation of power supply and eventually leads to a large error in the daily power line loss rate. For the problem of missing electricity consumption data, this study proposes a group method of data handling (GMDH) based… More >