Comparison of Hospital Building’s Energy Consumption Prediction Using Artificial Neural Networks, ANFIS, and LSTM Network

Since accurate load forecasting plays an important role in the improvisation of buildings and as described in EU’s “Green Deal”, financial resources saved through improvisation of the efficiency of buildings with social importance such as hospitals, will be the funds to support their mission, the so...

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Veröffentlicht in:	Energies (Basel) Jg. 15; H. 17; S. 6453
Hauptverfasser:	Panagiotou, Dimitrios K., Dounis, Anastasios I.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.09.2022
Schlagworte:	adaptive neuro-fuzzy adaptive inference system artificial neural networks Back propagation backpropagation algorithms Buildings Comparative analysis Electricity Emissions Energy consumption Energy efficiency Energy management Energy use Forecasting Forecasts and trends Genetic algorithms Greece Greenhouse gases Health facilities Hospitals long short-term memory networks Machine learning metaheuristic algorithms Neural networks Neurons Prediction theory Public buildings Public health Support vector machines Technology application Greece
ISSN:	1996-1073, 1996-1073
Online-Zugang:	Volltext
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