Power quality survey and analysis at educational institution loads

A survey of deep learning applications in cryptocurrency

“…230 Lack of accuracy in the prediction through deep learning algorithms Choose algorithms based on their properties when applying them to various modeling tasks Ensemble learning and other algorithms Rama Rao et al. 231 Ignorance of interactive behavior data across nodes or chains Design smart contracts to model the dynamic characteristics of interaction behavior, between different data on the chain Identification technique that can self-adapt to changes in the chain’s behavior Du et al. 232 Multi-objective, multi-level model design and application Maximize agent utility by modeling multi-task learning, and focus on global optimum Multi-objective architectures, transfer learning and encompass learning Poyatos et al.…”

“…Rao et al. 231 combined three classic ensemble learning algorithms (ensemble averaging, bagging, and stacking) to predict the hourly value of major cryptocurrencies. The proposed ensemble method is evaluated using traditional DL strategies combining LSTM, bidirectional (BiLSTM), and convolutional layers to achieve more accurate predictions.…”

Survey of a Power Quality Measurement Campaign in Low-Voltage Grids

“…However, the survey mostly consisted of qualitative data. To meet the requirements set in the standard, power quality has been validated for residential and public grids in Poland [6] and for an educational building in India [7]. Power quality parameter deviation caused by industrial customers in Estonia were studied in [8].…”