A review of data-driven building energy prediction
H Liu, J Liang, Y Liu, H Wu - Buildings, 2023 - mdpi.com
Building energy consumption prediction has a significant effect on energy control, design
optimization, retrofit evaluation, energy price guidance, and prevention and control of COVID …
optimization, retrofit evaluation, energy price guidance, and prevention and control of COVID …
Forecasting China's hydropower generation using a novel seasonal optimized multivariate grey model
Y Ren, L Xia, Y Wang - Technological Forecasting and Social Change, 2023 - Elsevier
Global warming and environmental degradation are essential issues that endanger human
survival. The conflict between rising carbon emissions and carbon neutrality goals has …
survival. The conflict between rising carbon emissions and carbon neutrality goals has …
Exploring artificial intelligence methods for energy prediction in healthcare Facilities: An In-Depth extended systematic review
M FatehiJananloo, H Stopps, JJ McArthur - Energy and Buildings, 2024 - Elsevier
Hospitals, due to their complexity and unique requirements, play a pivotal role in global
energy consumption patterns. This study conducted a comprehensive literature review …
energy consumption patterns. This study conducted a comprehensive literature review …
Predicting energy performances of buildings' envelope wall materials via the random forest algorithm
Purpose Numerous simulation software has been used to evaluate energy performance with
12% of the research focusing on long-term energy consumption prediction. This paper aims …
12% of the research focusing on long-term energy consumption prediction. This paper aims …
CO2 concentration forecasting in smart cities using a hybrid ARIMA–TFT model on multivariate time series IoT data
P Linardatos, V Papastefanopoulos… - Scientific reports, 2023 - nature.com
Carbon Dioxide (CO 2) is a significant contributor to greenhouse gas emissions and one of
the main drivers behind global warming and climate change. In spite of the global economic …
the main drivers behind global warming and climate change. In spite of the global economic …
Smart cities: The role of Internet of Things and machine learning in realizing a data-centric smart environment
This paper explores the concept of smart cities and the role of the Internet of Things (IoT)
and machine learning (ML) in realizing a data-centric smart environment. Smart cities …
and machine learning (ML) in realizing a data-centric smart environment. Smart cities …
Optimization in construction management using adaptive opposition slime mould algorithm
The purpose of this research study is to solve a four‐objective optimization problem in the
construction industry using a hybrid model that combines the slime mould algorithm (SMA) …
construction industry using a hybrid model that combines the slime mould algorithm (SMA) …
Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential …
Residential uses a significant amount of energy; hence, encouraging sustainability and
lessening environmental effects requires minimizing energy consumption in this sector. This …
lessening environmental effects requires minimizing energy consumption in this sector. This …
[HTML][HTML] Sustainable building optimization model for early-stage design
Buildings represent the largest potential for carbon reduction worldwide. This highlights the
need for a simulation and optimization method for energy management. The early design …
need for a simulation and optimization method for energy management. The early design …
Quantum-behaved particle swarm optimization based on solitons
S Fallahi, M Taghadosi - Scientific Reports, 2022 - nature.com
This paper introduces a novel variant of the quantum particle swarm optimization algorithm
based on the quantum concept of particle-like solitons as the most common solutions of the …
based on the quantum concept of particle-like solitons as the most common solutions of the …