Machine learning technology in biodiesel research: A review
Biodiesel has the potential to significantly contribute to making transportation fuels more
sustainable. Due to the complexity and nonlinearity of processes for biodiesel production …
sustainable. Due to the complexity and nonlinearity of processes for biodiesel production …
Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda
Artificial intelligence (AI) will transform business practices and industries and has the
potential to address major societal problems, including sustainability. Degradation of the …
potential to address major societal problems, including sustainability. Degradation of the …
Introducing the “15-Minute City”: Sustainability, resilience and place identity in future post-pandemic cities
The socio-economic impacts on cities during the COVID-19 pandemic have been brutal,
leading to increasing inequalities and record numbers of unemployment around the world …
leading to increasing inequalities and record numbers of unemployment around the world …
Artificial intelligence applications for microgrids integration and management of hybrid renewable energy sources
The integration of renewable energy sources (RESs) has become more attractive to provide
electricity to rural and remote areas, which increases the reliability and sustainability of the …
electricity to rural and remote areas, which increases the reliability and sustainability of the …
A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems
The optimal co-planning of the integrated energy system (IES) and machine learning (ML)
application on the multivariable prediction of IES parameters have mostly been carried out …
application on the multivariable prediction of IES parameters have mostly been carried out …
Solar photovoltaic Maximum Power Point Tracking controller optimization using Grey Wolf Optimizer: A performance comparison between bio-inspired and traditional …
Solar photovoltaic systems are widely used; however, their performance is bound to weather
conditions, depending on irradiation, temperature, and the effect of shadows. Maximum …
conditions, depending on irradiation, temperature, and the effect of shadows. Maximum …
A survey of machine learning models in renewable energy predictions
The use of renewable energy to reduce the effects of climate change and global warming
has become an increasing trend. In order to improve the prediction ability of renewable …
has become an increasing trend. In order to improve the prediction ability of renewable …
A comparative study of PSO-ANN, GA-ANN, ICA-ANN, and ABC-ANN in estimating the heating load of buildings' energy efficiency for smart city planning
Energy-efficiency is one of the critical issues in smart cities. It is an essential basis for
optimizing smart cities planning. This study proposed four new artificial intelligence (AI) …
optimizing smart cities planning. This study proposed four new artificial intelligence (AI) …
Towards intelligent building energy management: AI-based framework for power consumption and generation forecasting
Due to global warming and climate changes, buildings including residential and commercial
are significant contributors to energy consumption. To this end, net zero energy building …
are significant contributors to energy consumption. To this end, net zero energy building …
Prospective methodologies in hybrid renewable energy systems for energy prediction using artificial neural networks
This paper presents a comprehensive review of machine learning (ML) based approaches,
especially artificial neural networks (ANNs) in time series data prediction problems …
especially artificial neural networks (ANNs) in time series data prediction problems …