Network training error and sparsity are two critical factors in optimizing the model
parameters of existing neuro-evolution algorithms. Alleviating the curse of dimensionality in …

Currently, prediction stands as one of the most prominent areas of research. Enhancing the
accuracy and generalization capabilities of prediction models remains a crucial and ongoing …

To solve dynamic multi-objective optimization problems, evolutionary algorithms must be
capable of quickly and accurately tracking the changing Pareto front such that they can …

Accurate wind speed forecasting is crucial for wind energy development and utilization. The
non-linearity and non-stationarity of the wind speed leads to difficulties in its prediction …

Wind speed plays a pivotal role in ensuring the stability of power grid operations. However,
the inherent high volatility and non-stationarity of wind patterns pose significant challenges …

Accurate wind power forecasting (WPF) is vital for grid stability. Most existing studies rely on
the combination methods, and the multi-source information (MSI) related to the wind power …

It is crucial to predict the wind speed for the utilization of renewable wind energy and the
operation of transmission lines with increased capacity. The intermittency and stochastic …

Wind power generation plays a crucial role in promoting the transformation and
advancement of the power industry and fostering sustainable development in society …

Accurate short-term wind power prediction is crucial for the efficient and safe operation of
wind power systems. To enhance the accuracy of short-term wind power prediction, this …

Quantifying the complementary characteristics of the wind-photovoltaic-hydro (W-PV-H)
system under multiple uncertainties is very important for the planning and operation of W-PV …