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 …
[PDF][PDF] A comprehensive review of artificial intelligence and machine learning applications in energy sector
The energy industry worldwide is today confronted with several challenges, including
heightened levels of consumption and inefficiency, volatile patterns in demand and supply …
heightened levels of consumption and inefficiency, volatile patterns in demand and supply …
[HTML][HTML] Smart and Sustainable Energy Consumption: A Bibliometric Review and Visualization
This paper presents a comprehensive bibliometric review and visualization of smart and
sustainable energy consumption, delving into the challenges and opportunities of …
sustainable energy consumption, delving into the challenges and opportunities of …
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 …
Short-term occupancy forecasting for a smart home using optimized weight updates based on ga and PSO algorithms for an LSTM network
In this work, we provide a smart home occupancy prediction technique based on
environmental variables such as CO 2, noise, and relative temperature via our machine …
environmental variables such as CO 2, noise, and relative temperature via our machine …
[HTML][HTML] Domestic hot water consumption prediction models suited for dwellings in central-southern parts of Chile
Domestic hot water (DHW) consumption in dwellings can play a key role in the development
of policies that are focused on energy poverty, and in improving energy efficiency, among …
of policies that are focused on energy poverty, and in improving energy efficiency, among …
Comparison of hospital building's energy consumption prediction using artificial neural networks, ANFIS, and LSTM network
Since accurate load forecasting plays an important role in the improvisation of buildings and
as described in EU's “Green Deal”, financial resources saved through improvisation of the …
as described in EU's “Green Deal”, financial resources saved through improvisation of the …
Design of ensemble forecasting models for home energy management systems
The increasing levels of energy consumption worldwide is raising issues with respect to
surpassing supply limits, causing severe effects on the environment, and the exhaustion of …
surpassing supply limits, causing severe effects on the environment, and the exhaustion of …
A Data-Driven Forecasting Strategy to Predict Continuous Hourly Energy Demand in Smart Buildings
Smart buildings seek to have a balance between energy consumption and occupant
comfort. To make this possible, smart buildings need to be able to foresee sudden changes …
comfort. To make this possible, smart buildings need to be able to foresee sudden changes …
[HTML][HTML] Federated learning framework for prediction of net energy demand in transactive energy communities
The implementation of transactive energy systems in communities requires new control
mechanisms for enabling end-use energy trading. To optimize the operation of these …
mechanisms for enabling end-use energy trading. To optimize the operation of these …