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Deep learning versus traditional machine learning methods for aggregated energy demand prediction
Despite the fact that a wide range of machine learning methods have been applied to probabilistic energy prediction, the deep learning ones certainly ...
文献获取Deep belief network based ensemble approach for cooling load forecasting of air-conditioning system
Due to the high energy consumption in buildings, cooling load forecasting plays a crucial role in the planning, control and operation of heating, ventil...
A Novel Ensemble Deep Learning Model for Building Energy Consumption Forecast
The issue of energy limitation has gained attention as a crisis faced by societies. Buildings play a major role, in energy consumption making it crucial...
A Sustainable Development for Building Energy Consumption Based on Improved Rafflesia Optimization Algorithm with Feature Selection ...
building energy consumption based on the improved rafflesia optimization algorithm (ROA) with feature selection and ensemble deep learning is proposed i...
Personalized federated learning for buildings energy consumption forecasting
Buildings' energy consumption forecasting is critical for energy saving and building maintenance. However, most studies only focus on centralized learni...
Energy-driven TBM health status estimation with a hybrid deep learning approach
(1) fully extracting and utilizing the energy consumption information in every regard to predict TBM health performance; (2) providing a good one-step-...
A deep learning approach for energy management systems in smart buildings towards a low-carbon economy
Addressing the issue of cold load prediction in building energy systems, a multi-modal fusion deep learning approach is proposed. This method constructs...
Advanced computing to support urban climate neutrality
Deep learningTime series forecastingEnergy managementTraffic managementFleet managementClimate neutralityAchieving climate neutrality in cities is a maj...
A novel deep learning ensemble model based on two-stage feature selection and intelligent optimization for water quality prediction
Accurate prediction of effluent total nitrogen (E-TN) can assist in feed-forward control of wastewater treatment plants (WWTPs) to ensure effluent compl...
Energy consumption prediction of the cold source system based on GraphSAGE
(such as recurrent neural network,deep belief network),as well as ensemble learning and reinforcement learning all provide new ways for energy consumpti...
