A review of wind speed and wind power forecasting with deep neural networks
The use of wind power, a pollution-free and renewable form of energy, to generate electricity
has attracted increasing attention. However, intermittent electricity generation resulting from …
has attracted increasing attention. However, intermittent electricity generation resulting from …
Machine learning driven smart electric power systems: Current trends and new perspectives
MS Ibrahim, W Dong, Q Yang - Applied Energy, 2020 - Elsevier
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
Dispersed foraging slime mould algorithm: Continuous and binary variants for global optimization and wrapper-based feature selection
The slime mould algorithm (SMA) is a logical swarm-based stochastic optimizer that is easy
to understand and has a strong optimization capability. However, the SMA is not suitable for …
to understand and has a strong optimization capability. However, the SMA is not suitable for …
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 …
Mean–variance portfolio optimization using machine learning-based stock price prediction
The success of portfolio construction depends primarily on the future performance of stock
markets. Recent developments in machine learning have brought significant opportunities to …
markets. Recent developments in machine learning have brought significant opportunities to …
Boosting whale optimization with evolution strategy and Gaussian random walks: An image segmentation method
Stochastic optimization has been found in many applications, especially for several local
optima problems, because of their ability to explore and exploit various zones of the feature …
optima problems, because of their ability to explore and exploit various zones of the feature …
Image segmentation of Leaf Spot Diseases on Maize using multi-stage Cauchy-enabled grey wolf algorithm
Grey wolf optimizer (GWO) is a widespread metaphor-based algorithm based on the
enhanced variants of velocity-free particle swarm optimizer with proven defects and …
enhanced variants of velocity-free particle swarm optimizer with proven defects and …
Boosted kernel search: Framework, analysis and case studies on the economic emission dispatch problem
R Dong, H Chen, AA Heidari, H Turabieh… - Knowledge-Based …, 2021 - Elsevier
In recent years, a variety of meta-heuristic nature-inspired algorithms have been proposed to
solve complex optimization problems. However, these algorithms suffer from the …
solve complex optimization problems. However, these algorithms suffer from the …
A convolutional Transformer-based truncated Gaussian density network with data denoising for wind speed forecasting
Y Wang, H Xu, M Song, F Zhang, Y Li, S Zhou, L Zhang - Applied Energy, 2023 - Elsevier
Wind speed forecasting plays an important role in the stable operation of wind energy power
systems. However, accurate and reliable wind speed forecasting faces four challenges: how …
systems. However, accurate and reliable wind speed forecasting faces four challenges: how …
Boosting slime mould algorithm for parameter identification of photovoltaic models
Estimating the photovoltaic model's unknown parameters efficiently and accurately can
determine the solar cell's efficacy in converting the solar energy into electricity. For this …
determine the solar cell's efficacy in converting the solar energy into electricity. For this …