[HTML][HTML] Artificial intelligence and machine learning in energy systems: A bibliographic perspective
Economic development and the comfort-loving nature of human beings in recent years have
resulted in increased energy demand. Since energy resources are scarce and should be …
resulted in increased energy demand. Since energy resources are scarce and should be …
Electricity load forecasting: a systematic review
IK Nti, M Teimeh, O Nyarko-Boateng… - Journal of Electrical …, 2020 - Springer
The economic growth of every nation is highly related to its electricity infrastructure, network,
and availability since electricity has become the central part of everyday life in this modern …
and availability since electricity has become the central part of everyday life in this modern …
A machine learning approach on the relationship among solar and wind energy production, coal consumption, GDP, and CO2 emissions
China, India, and the USA are the world's biggest energy consumers and CO 2 emitters.
Being the leading contributors to climate change, these economies are also at the core of …
Being the leading contributors to climate change, these economies are also at the core of …
Methods of forecasting electric energy consumption: A literature review
RV Klyuev, ID Morgoev, AD Morgoeva, OA Gavrina… - Energies, 2022 - mdpi.com
Balancing the production and consumption of electricity is an urgent task. Its implementation
largely depends on the means and methods of planning electricity production. Forecasting is …
largely depends on the means and methods of planning electricity production. Forecasting is …
[HTML][HTML] Energy consumption prediction by using machine learning for smart building: Case study in Malaysia
Abstract Building Energy Management System (BEMS) has been a substantial topic
nowadays due to its importance in reducing energy wastage. However, the performance of …
nowadays due to its importance in reducing energy wastage. However, the performance of …
Smart Energy Management: A Comparative Study of Energy Consumption Forecasting Algorithms for an Experimental Open-Pit Mine
The mining industry's increased energy consumption has resulted in a slew of climate-
related effects on the environment, many of which have direct implications for humanity's …
related effects on the environment, many of which have direct implications for humanity's …
A machine learning and deep learning based approach to predict the thermal performance of phase change material integrated building envelope
This study aims to develop a machine learning and deep learning-based model for thermal
performance prediction of PCM integrated roof building. Performance prediction is carried …
performance prediction of PCM integrated roof building. Performance prediction is carried …
Ensemble learning for electricity consumption forecasting in office buildings
This paper presents three ensemble learning models for short term load forecasting.
Machine learning has evolved quickly in recent years, leading to novel and advanced …
Machine learning has evolved quickly in recent years, leading to novel and advanced …
Electricity demand forecasting using a novel time series ensemble technique
Accurate and efficient demand forecasting is essential to grid stability, supply, and
management in today's electricity markets. Due to the complex pattern of electric power …
management in today's electricity markets. Due to the complex pattern of electric power …
Time series forecasting with multi-headed attention-based deep learning for residential energy consumption
Predicting residential energy consumption is tantamount to forecasting a multivariate time
series. A specific window for several sensor signals can induce various features extracted to …
series. A specific window for several sensor signals can induce various features extracted to …