Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Machine learning for estimation of building energy consumption and performance: a review
Ever growing population and progressive municipal business demands for constructing new
buildings are known as the foremost contributor to greenhouse gasses. Therefore …
buildings are known as the foremost contributor to greenhouse gasses. Therefore …
Machine learning-enabled analysis of product distribution and composition in biomass-coal co-pyrolysis
Co-pyrolysis of biomass and coal presents a promising opportunity for large-scale biomass
utilization while reducing fossil fuel consumption. However, this process is highly complex …
utilization while reducing fossil fuel consumption. However, this process is highly complex …
Deep learning framework to forecast electricity demand
The increasing world population and availability of energy hungry smart devices are major
reasons for alarmingly high electricity consumption in the current times. So far, various …
reasons for alarmingly high electricity consumption in the current times. So far, various …
Building energy load forecasting using deep neural networks
Ensuring sustainability demands more efficient energy management with minimized energy
wastage. Therefore, the power grid of the future should provide an unprecedented level of …
wastage. Therefore, the power grid of the future should provide an unprecedented level of …
Modeling techniques used in building HVAC control systems: A review
The appropriate application of advanced control strategies in Heating, Ventilation, and Air-
conditioning (HVAC) systems is key to improving the energy efficiency of buildings …
conditioning (HVAC) systems is key to improving the energy efficiency of buildings …
Deep neural networks for energy load forecasting
Smartgrids of the future promise unprecedented flexibility in energy management. Therefore,
accurate predictions/forecasts of energy demands (loads) at individual site and aggregate …
accurate predictions/forecasts of energy demands (loads) at individual site and aggregate …
Predicting the energy consumption in buildings using the optimized support vector regression model
W Cai, X Wen, C Li, J Shao, J Xu - Energy, 2023 - Elsevier
One of the most significant axes of regional, national, and worldwide energy policy is energy
efficiency in building design. In particular, the energy efficiency of HVAC systems is of …
efficiency in building design. In particular, the energy efficiency of HVAC systems is of …
Modelling of a multi-stage energy management control routine for energy demand forecasting, flexibility, and optimization of smart communities using a Recurrent …
This paper proposes an innovative algorithm for community energy management control,
able to involve customers in energy trading by exploiting their potential energy flexibility. The …
able to involve customers in energy trading by exploiting their potential energy flexibility. The …
Transfer learning with deep neural networks for model predictive control of HVAC and natural ventilation in smart buildings
Advanced control strategies are central components of smart buildings. For model-based
control algorithms, the quality of the model that represents building systems and dynamics is …
control algorithms, the quality of the model that represents building systems and dynamics is …
A comprehensive review on the application of artificial neural networks in building energy analysis
This paper presents a comprehensive review of the significant studies exploited Artificial
Neural Networks (ANNs) in BEA (Building Energy Analysis). To achieve a full coverage of …
Neural Networks (ANNs) in BEA (Building Energy Analysis). To achieve a full coverage of …