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[HTML][HTML] Forecasting solar power generation using evolutionary mating algorithm-deep neural networks
This paper proposes an integration of recent metaheuristic algorithm namely Evolutionary
Mating Algorithm (EMA) in optimizing the weights and biases of deep neural networks …
Mating Algorithm (EMA) in optimizing the weights and biases of deep neural networks …
[HTML][HTML] Integration of smart grid with Industry 5.0: Applications, challenges and solutions
Introduction In this study, an investigation of the nexus between state-of-the-art technology
and green industrial processes with a view to how smart grid systems can be incorporated …
and green industrial processes with a view to how smart grid systems can be incorporated …
[HTML][HTML] Ultra-Short-Term Photovoltaic Power Prediction by NRGA-BiLSTM Considering Seasonality and Periodicity of Data
Photovoltaic (PV) power generation is highly stochastic and intermittent, which poses a
challenge to the planning and operation of existing power systems. To enhance the …
challenge to the planning and operation of existing power systems. To enhance the …
An error-corrected deep Autoformer model via Bayesian optimization algorithm and secondary decomposition for photovoltaic power prediction
Accurate PV power prediction is crucial for stable grid operation and rational dispatch.
However, due to the instability of PV power generation, PV power prediction still has great …
However, due to the instability of PV power generation, PV power prediction still has great …
Method and validation of coal mine gas concentration prediction by integrating PSO algorithm and LSTM network
Gas concentration monitoring is an effective method for predicting gas disasters in mines. In
response to the shortcomings of low efficiency and accuracy in conventional gas …
response to the shortcomings of low efficiency and accuracy in conventional gas …
Distributed-regional photovoltaic power generation prediction with limited data: A robust autoregressive transfer learning method
This paper proposes a distributed regional photovoltaic (PV) power generation prediction
method to address scenarios with a very high percentage of missing data. The proposed …
method to address scenarios with a very high percentage of missing data. The proposed …
Systematic literature review on Industry 5.0: current status and future research directions with insights for the Asia Pacific countries
The rapid rise of research on Industry 5.0 has garnered significant attention, but the literature
remains fragmented across various fields. Our systematic review of 98 articles, published …
remains fragmented across various fields. Our systematic review of 98 articles, published …
Energy Load Forecasting Techniques in Smart Grids: A Cross-Country Comparative Analysis
Energy management systems allow the Smart Grids industry to track, improve, and regulate
energy use. Particularly, demand-side management is regarded as a crucial component of …
energy use. Particularly, demand-side management is regarded as a crucial component of …
Explainable AI and optimized solar power generation forecasting model based on environmental conditions
This paper proposes a model called X-LSTM-EO, which integrates explainable artificial
intelligence (XAI), long short-term memory (LSTM), and equilibrium optimizer (EO) to reliably …
intelligence (XAI), long short-term memory (LSTM), and equilibrium optimizer (EO) to reliably …
[HTML][HTML] Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis
This article presents deep learning frameworks for predicting electricity demand in the
Western region of Bangladesh, utilizing Artificial Neural Network (ANN) and Adaptive Neuro …
Western region of Bangladesh, utilizing Artificial Neural Network (ANN) and Adaptive Neuro …