[HTML][HTML] A systematic review on automated human emotion recognition using electroencephalogram signals and artificial intelligence
Abstract Brain-Computer Interaction (BCI) system intelligence has become more dependent
on electroencephalogram (EEG)-based emotion recognition because of the numerous …
on electroencephalogram (EEG)-based emotion recognition because of the numerous …
A state of art review on estimation of solar radiation with various models
Solar radiation is free, and very useful input for most sectors such as heat, health, tourism,
agriculture, and energy production, and it plays a critical role in the sustainability of …
agriculture, and energy production, and it plays a critical role in the sustainability of …
[HTML][HTML] Environmental optimization of warm mix asphalt (WMA) design with recycled concrete aggregates (RCA) inclusion through artificial intelligence (AI) …
R Polo-Mendoza, G Martinez-Arguelles… - Results in …, 2023 - Elsevier
Abstract Warm Mix Asphalts (WMAs) are asphalt concretes produced at lower temperatures
than traditional Hot Mix Asphalts (HMAs). Nonetheless, the above is not enough to diminish …
than traditional Hot Mix Asphalts (HMAs). Nonetheless, the above is not enough to diminish …
A novel machine learning approach for solar radiation estimation
Solar irradiation (Rs) is the electromagnetic radiation energy emitted by the Sun. It plays a
crucial role in sustaining life on Earth by providing light, heat, and energy. Furthermore, it …
crucial role in sustaining life on Earth by providing light, heat, and energy. Furthermore, it …
Site suitability assessment for solar power plants in Bangladesh: A GIS-based analytical hierarchy process (AHP) and multi-criteria decision analysis (MCDA) …
Solar power plants are important alternatives to fossil fuel-based power plants because they
reduce greenhouse gas emissions and mitigate the effects of climate change. The potential …
reduce greenhouse gas emissions and mitigate the effects of climate change. The potential …
Short-term solar irradiance forecasting based on a novel Bayesian optimized deep Long Short-Term Memory neural network
Accurate forecasting is indispensable for improving solar renewables integration and
minimizing the effects of solar energy's intermittency. Existing research on time series solar …
minimizing the effects of solar energy's intermittency. Existing research on time series solar …
[HTML][HTML] Forecasting energy consumption demand of customers in smart grid using Temporal Fusion Transformer (TFT)
Energy consumption prediction has always remained a concern for researchers because of
the rapid growth of the human population and customers joining smart grids network for …
the rapid growth of the human population and customers joining smart grids network for …
Deep learning based long-term global solar irradiance and temperature forecasting using time series with multi-step multivariate output
Solar radiation's intermittent and fluctuating nature poses severe limitations for most
applications. Accurate prediction of solar radiation is an essential factor in predicting the …
applications. Accurate prediction of solar radiation is an essential factor in predicting the …
[HTML][HTML] Automatic pavement damage predictions using various machine learning algorithms: Evaluation and comparison
R Nyirandayisabye, H Li, Q Dong, T Hakuzweyezu… - Results in …, 2022 - Elsevier
In recent years, different technologies based on Machine Learning (ML) algorithms have
been developed to evaluate road distress quality and help with pavement maintenance …
been developed to evaluate road distress quality and help with pavement maintenance …
Hybrid convolutional neural network-multilayer perceptron model for solar radiation prediction
Urgent transition from the dependence on fossil fuels towards renewable energies requires
more solar photovoltaic power to be connected to the electricity grids, with reliable supply …
more solar photovoltaic power to be connected to the electricity grids, with reliable supply …