Electricity Consumption Forecast of Clusters of Buildings Based on Recurrent Neural Networks

Author:

Golovinski Pavel1,Vasenin Dmitrii2,Savvin Nikita1,Rinaldi Stefano2,Pasetti Marco2

Affiliation:

1. Voronezh State Technical University,I.S Surovtseva,Department of Innovation and Building Physics named after Professor,Voronezh,Russian Federation

2. Università degli Studi di Brescia,Department of Information Engineering,Brescia,Italy

Publisher

IEEE

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Meta-Survey on Intelligent Energy-Efficient Buildings;Big Data and Cognitive Computing;2024-07-30

2. Incorporating Seasonal Features in Data Imputation Methods for Power Demand Time Series;IEEE Access;2024

3. Tools for Analysis of Treatment Dynamics and Outcomes for Personalized Medicine in Asthma;2023 IEEE 17th International Conference on Application of Information and Communication Technologies (AICT);2023-10-18

4. Long-Term Electrical Energy Forecasting of the Residential Sector Using the LSTM Model: The Italian Use Case;2023 International Conference on Future Energy Solutions (FES);2023-06-12

5. Structural Optimization of Interuniversity Campus with System Analysis of the Territorial Dispersion of Residential and Educational Facilities;2023 6th International Conference on Energy Conservation and Efficiency (ICECE);2023-03-15

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