Roles of artificial intelligence in construction engineering and management: A critical review and future trends
With the extensive adoption of artificial intelligence (AI), construction engineering and
management (CEM) is experiencing a rapid digital transformation. Since AI-based solutions …
management (CEM) is experiencing a rapid digital transformation. Since AI-based solutions …
Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption—A systematic review
The building sector accounts for 36% of the total global energy usage and 40% of
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …
Building energy consumption prediction for residential buildings using deep learning and other machine learning techniques
The high proportion of energy consumed in buildings has engendered the manifestation of
many environmental problems which deploy adverse impacts on the existence of mankind …
many environmental problems which deploy adverse impacts on the existence of mankind …
Predicting residential energy consumption using CNN-LSTM neural networks
The rapid increase in human population and development in technology have sharply
raised power consumption in today's world. Since electricity is consumed simultaneously as …
raised power consumption in today's world. Since electricity is consumed simultaneously as …
Load forecasting techniques for power system: Research challenges and survey
The main and pivot part of electric companies is the load forecasting. Decision-makers and
think tank of power sectors should forecast the future need of electricity with large accuracy …
think tank of power sectors should forecast the future need of electricity with large accuracy …
Applications of artificial intelligence in engineering and manufacturing: a systematic review
Engineering and manufacturing processes and systems designs involve many challenges,
such as dynamism, chaotic behaviours, and complexity. Of late, the arrival of big data, high …
such as dynamism, chaotic behaviours, and complexity. Of late, the arrival of big data, high …
[HTML][HTML] A building energy consumption prediction model based on rough set theory and deep learning algorithms
L Lei, W Chen, B Wu, C Chen, W Liu - Energy and Buildings, 2021 - Elsevier
The efficient and accurate prediction of building energy consumption can improve the
management of power systems. In this paper, the rough set theory was used to reduce the …
management of power systems. In this paper, the rough set theory was used to reduce the …
Vector field-based support vector regression for building energy consumption prediction
Building energy consumption prediction plays an irreplaceable role in energy planning,
management, and conservation. Data-driven approaches, such as artificial neural networks …
management, and conservation. Data-driven approaches, such as artificial neural networks …
A review of deep learning models for time series prediction
Z Han, J Zhao, H Leung, KF Ma… - IEEE Sensors Journal, 2019 - ieeexplore.ieee.org
In order to approximate the underlying process of temporal data, time series prediction has
been a hot research topic for decades. Developing predictive models plays an important role …
been a hot research topic for decades. Developing predictive models plays an important role …
Forecasting energy use in buildings using artificial neural networks: A review
J Runge, R Zmeureanu - Energies, 2019 - mdpi.com
During the past century, energy consumption and associated greenhouse gas emissions
have increased drastically due to a wide variety of factors including both technological and …
have increased drastically due to a wide variety of factors including both technological and …