Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy storage
D Rangel-Martinez, KDP Nigam… - … Research and Design, 2021 - Elsevier
This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …
manufacturing sectors that have a considerable impact on sustainability and the …
State of the art of machine learning models in energy systems, a systematic review
Machine learning (ML) models have been widely used in the modeling, design and
prediction in energy systems. During the past two decades, there has been a dramatic …
prediction in energy systems. During the past two decades, there has been a dramatic …
Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
Accurate runoff estimation is crucial for optimal reservoir operation and irrigation purposes.
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
Sustainable business models: A review
S Nosratabadi, A Mosavi, S Shamshirband… - Sustainability, 2019 - mdpi.com
During the past two decades of e-commerce growth, the concept of a business model has
become increasingly popular. More recently, the research on this realm has grown rapidly …
become increasingly popular. More recently, the research on this realm has grown rapidly …
A new hybrid grey wolf optimizer-feature weighted-multiple kernel-support vector regression technique to predict TBM performance
Full-face tunnel boring machine (TBM) is a modern and efficient tunnel construction
equipment. A reliable and accurate TBM performance (like penetration rate, PR) prediction …
equipment. A reliable and accurate TBM performance (like penetration rate, PR) prediction …
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 …
Artificial intelligence evolution in smart buildings for energy efficiency
The emerging concept of smart buildings, which requires the incorporation of sensors and
big data (BD) and utilizes artificial intelligence (AI), promises to usher in a new age of urban …
big data (BD) and utilizes artificial intelligence (AI), promises to usher in a new age of urban …
[HTML][HTML] Prediction of the effects of climate change on hydroelectric generation, electricity demand, and emissions of greenhouse gases under climatic scenarios and …
LN Guo, C She, DB Kong, SL Yan, YP Xu… - Energy Reports, 2021 - Elsevier
In this study, an attempt is made to manage the gap between energy demand and energy
supply by predicting hydropower production, energy demand, and greenhouse gas …
supply by predicting hydropower production, energy demand, and greenhouse gas …
Evaluating the performances of several artificial intelligence methods in forecasting daily streamflow time series for sustainable water resources management
W Niu, Z Feng - Sustainable Cities and Society, 2021 - Elsevier
Accurate runoff forecasting plays an important role in guaranteeing the sustainable
utilization and management of water resources. Artificial intelligence methods can provide …
utilization and management of water resources. Artificial intelligence methods can provide …
Comprehensive review of deep reinforcement learning methods and applications in economics
The popularity of deep reinforcement learning (DRL) applications in economics has
increased exponentially. DRL, through a wide range of capabilities from reinforcement …
increased exponentially. DRL, through a wide range of capabilities from reinforcement …