[HTML][HTML] Air temperature forecasting using machine learning techniques: a review
Efforts to understand the influence of historical climate change, at global and regional levels,
have been increasing over the past decade. In particular, the estimates of air temperatures …
have been increasing over the past decade. In particular, the estimates of air temperatures …
Optimisation of energy management in commercial buildings with weather forecasting inputs: A review
Abstract Information about the patterns that govern the energy demand and onsite
generation can generate significant savings in the range of 15–30% in most cases and thus …
generation can generate significant savings in the range of 15–30% in most cases and thus …
Prediction of hourly energy consumption in buildings based on a feedback artificial neural network
PA Gonzalez, JM Zamarreno - Energy and buildings, 2005 - Elsevier
In this paper a new approach for short-term load prediction in buildings is shown. The
method is based on a special kind of artificial neural network (ANN), which feeds back a part …
method is based on a special kind of artificial neural network (ANN), which feeds back a part …
[HTML][HTML] Utilizing time series data from 1961 to 2019 recorded around the world and machine learning to create a Global Temperature Change Prediction Model
SM Malakouti - Case Studies in Chemical and Environmental …, 2023 - Elsevier
Since 1880, the Earth's temperature has increased at a pace of 0.14° Fahrenheit (0.08°
Celsius) every decade; however, the rate of warming since 1981 is more than double that, at …
Celsius) every decade; however, the rate of warming since 1981 is more than double that, at …
[HTML][HTML] Ambient temperature and solar irradiance forecasting prediction horizon sensitivity analysis
J Ramirez-Vergara, LB Bosman, WD Leon-Salas… - Machine Learning with …, 2021 - Elsevier
Selecting the correct weather forecasting technique is a crucial task when planning an
efficient solar energy generation system. Estimating accurate solar photovoltaic systems …
efficient solar energy generation system. Estimating accurate solar photovoltaic systems …
Hourly temperature forecasting using abductive networks
RE Abdel-Aal - Engineering Applications of Artificial Intelligence, 2004 - Elsevier
Hourly temperature forecasts are important for electrical load forecasting and other
applications in industry, agriculture, and the environment. Modern machine learning …
applications in industry, agriculture, and the environment. Modern machine learning …
Wavelet-based multi-resolution analysis and artificial neural networks for forecasting temperature and thermal power consumption
J Eynard, S Grieu, M Polit - Engineering Applications of Artificial …, 2011 - Elsevier
As part of the OptiEnR research project, the present paper deals with outdoor temperature
and thermal power consumption forecasting. This project focuses on optimizing the …
and thermal power consumption forecasting. This project focuses on optimizing the …
Review of onsite temperature and solar forecasting models to enable better building design and operations
Advanced building controls and energy optimization for new constructions and retrofits rely
on accurate weather data. Traditionally, most studies utilize airport weather information as …
on accurate weather data. Traditionally, most studies utilize airport weather information as …
Model predictive control under forecast uncertainty for optimal operation of buildings with integrated solar systems
In this paper, we explore intelligent operation strategies, based on stochastic model
predictive control (SMPC), for optimal utilization of solar energy in buildings with integrated …
predictive control (SMPC), for optimal utilization of solar energy in buildings with integrated …
Optimizing K-means clustering center selection with density-based spatial cluster in radial basis function neural network for load forecasting of smart solar microgrid
T Nguyen Da, MY Cho, P Nguyen Thanh - Electrical Engineering, 2024 - Springer
Many researchers have investigated estimating and forecasting load power by utilizing
many approaches and techniques in neural networks. In this case study, a novel method is …
many approaches and techniques in neural networks. In this case study, a novel method is …