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 …
Carbon emission prediction models: A review
Y **, A Sharifi, Z Li, S Chen, S Zeng, S Zhao - Science of The Total …, 2024 - Elsevier
Amidst growing concerns over the greenhouse effect, especially its consequential impacts,
establishing effective Carbon Emission Prediction Models (CEPMs) to comprehend and …
establishing effective Carbon Emission Prediction Models (CEPMs) to comprehend and …
Dispersed foraging slime mould algorithm: Continuous and binary variants for global optimization and wrapper-based feature selection
J Hu, W Gui, AA Heidari, Z Cai, G Liang, H Chen… - Knowledge-Based …, 2022 - Elsevier
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 …
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 …
Mean–variance portfolio optimization using machine learning-based stock price prediction
W Chen, H Zhang, MK Mehlawat, L Jia - Applied soft computing, 2021 - Elsevier
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 …
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 …
A wind speed forecasting system for the construction of a smart grid with two-stage data processing based on improved ELM and deep learning strategies
The operation and scheduling management of smart grids are important aspects, and wind
speed forecasting modules are indispensable in wind power system management …
speed forecasting modules are indispensable in wind power system management …
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 …
Weather impact on solar farm performance: a comparative analysis of machine learning techniques
Forecasting the performance and energy yield of photovoltaic (PV) farms is crucial for
establishing the economic sustainability of a newly installed system. The present study aims …
establishing the economic sustainability of a newly installed system. The present study aims …
Boosting whale optimization with evolution strategy and Gaussian random walks: An image segmentation method
AG Hussien, AA Heidari, X Ye, G Liang, H Chen… - Engineering with …, 2023 - Springer
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 …