AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …
components and functionalities required for analyzing and operating buildings. However, in …
A review of machine learning in building load prediction
The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …
opportunities for applying machine learning to building energy system modeling and …
A review of strategies for building energy management system: Model predictive control, demand side management, optimization, and fault detect & diagnosis
D Mariano-Hernández, L Hernández-Callejo… - Journal of Building …, 2021 - Elsevier
Building energy use is expected to grow by more than 40% in the next 20 years. Electricity
remains the largest energy source consumed by buildings, and that demand is growing. To …
remains the largest energy source consumed by buildings, and that demand is growing. To …
A review of the-state-of-the-art in data-driven approaches for building energy prediction
Building energy prediction plays a vital role in developing a model predictive controller for
consumers and optimizing energy distribution plan for utilities. Common approaches for …
consumers and optimizing energy distribution plan for utilities. Common approaches for …
Machine learning applications in urban building energy performance forecasting: A systematic review
In developed countries, buildings are involved in almost 50% of total energy use and 30% of
global green-house gas emissions. Buildings' operational energy is highly dependent on …
global green-house gas emissions. Buildings' operational energy is highly dependent on …
Multi-sequence LSTM-RNN deep learning and metaheuristics for electric load forecasting
Short term electric load forecasting plays a crucial role for utility companies, as it allows for
the efficient operation and management of power grid networks, optimal balancing between …
the efficient operation and management of power grid networks, optimal balancing between …
Forecasting energy consumption time series using machine learning techniques based on usage patterns of residential householders
Energy consumption in buildings is increasing because of social development and
urbanization. Forecasting the energy consumption in buildings is essential for improving …
urbanization. Forecasting the energy consumption in buildings is essential for improving …
Systematic review of deep learning and machine learning for building energy
S Ardabili, L Abdolalizadeh, C Mako, B Torok… - Frontiers in Energy …, 2022 - frontiersin.org
The building energy (BE) management plays an essential role in urban sustainability and
smart cities. Recently, the novel data science and data-driven technologies have shown …
smart cities. Recently, the novel data science and data-driven technologies have shown …
Data analytics in the supply chain management: Review of machine learning applications in demand forecasting
A Aamer, LP Eka Yani… - Operations and Supply …, 2020 - journal.oscm-forum.org
In today's fast-paced global economy coupled with the availability of mobile internet and
social networks, several business models have been disrupted. This disruption brings a …
social networks, several business models have been disrupted. This disruption brings a …
Novel neural network optimized by electrostatic discharge algorithm for modification of buildings energy performance
AM Fallah, E Ghafourian, L Shahzamani Sichani… - Sustainability, 2023 - mdpi.com
Proper analysis of building energy performance requires selecting appropriate models for
handling complicated calculations. Machine learning has recently emerged as a promising …
handling complicated calculations. Machine learning has recently emerged as a promising …