Energy and sustainable development in smart cities: An overview
Smart cities are an innovative concept for managing metropolitan areas to increase their
residents' sustainability and quality of life. This article examines the management and …
residents' sustainability and quality of life. This article examines the management and …
Data-driven tools for building energy consumption prediction: A review
The development of data-driven building energy consumption prediction models has gained
more attention in research due to its relevance for energy planning and conservation …
more attention in research due to its relevance for energy planning and conservation …
Machine learning for performance prediction in smart buildings: Photovoltaic self-consumption and life cycle cost optimization
The application of Photovoltaic (PV) system in buildings is growing rapidly in response to the
need for clean energy sources and building decarbonization targets. Nonetheless …
need for clean energy sources and building decarbonization targets. Nonetheless …
[HTML][HTML] Challenges of artificial intelligence development in the context of energy consumption and impact on climate change
With accelerating climate change and rising global energy consumption, the application of
artificial intelligence (AI) and machine learning (ML) has emerged as a crucial tool for …
artificial intelligence (AI) and machine learning (ML) has emerged as a crucial tool for …
An analysis of the energy consumption forecasting problem in smart buildings using LSTM
This work explores the process of predicting energy consumption in smart buildings based
on the consumption of devices and appliances. Particularly, this work studies the process of …
on the consumption of devices and appliances. Particularly, this work studies the process of …
[HTML][HTML] Statistical comparison of time series models for forecasting brazilian monthly energy demand using economic, industrial, and climatic exogenous variables
Energy demand forecasting is crucial for effective resource management within the energy
sector and is aligned with the objectives of Sustainable Development Goal 7 (SDG7). This …
sector and is aligned with the objectives of Sustainable Development Goal 7 (SDG7). This …
Prediction of thermal energy demand using fuzzy-based models synthesized with metaheuristic algorithms
Increasing consumption of energy calls for proper approximation of demand towards a
sustainable and cost-effective development. In this work, novel hybrid methodologies aim to …
sustainable and cost-effective development. In this work, novel hybrid methodologies aim to …
IoT-Enabled energy conservation in residential Buildings: Machine learning models for analyzing annual solar power consumption
This study investigates enhancing the self-consumption of solar panels by integrating
thermal and electrical energy storage using lithium-ion batteries in a duplex building over a …
thermal and electrical energy storage using lithium-ion batteries in a duplex building over a …
Comparison of machine learning algorithms for evaluating building energy efficiency using big data analytics
Purpose This study aims to compare and evaluate the application of commonly used
machine learning (ML) algorithms used to develop models for assessing energy efficiency of …
machine learning (ML) algorithms used to develop models for assessing energy efficiency of …
[HTML][HTML] Prediction method of energy consumption for high building based on LMBP neural network
R Lei, J Yin - Energy Reports, 2022 - Elsevier
With the power consumption of high-rise buildings rising year by year, energy consumption
of high-rise buildings has become the main object of energy-saving supervision and …
of high-rise buildings has become the main object of energy-saving supervision and …