Reducing sailing costs, time and emissions are three important decision-making objectives
for ship operators. In this paper, a multi-objective decision model for liner shipping is …

Human activities and climate change have exacerbated the frequency of extreme weather
events such as rainstorms and floods, which makes it difficult to accurately quantify the …

The inherent volatility and randomness of PV output has posed a severe danger to the safe
and stable functioning of power systems in recent years, as grid-connected PV capacity has …

Surrogate-assisted multi-objective evolutionary algorithms are powerful techniques to solve
computationally expensive multi-objective optimization problems. In this paper, we propose …

Photovoltaic (PV) power interval prediction can provide a variation range of prediction
results, which is of great significance to promoting the optimization of power grid dispatching …

Quantitative structure-activity relationship modeling techniques are widely employed in
diverse areas of chemistry, including environmental risk assessment of compounds and …

In this research, a unique approach to provide communication service for terrestrial
receivers via using unmanned aerial vehicle-enabled visible light communication is …

Dynamical systems that exhibit a high degree of sensitivity to the parameters of their initial
states are referred to as chaotic. Natural selection and the process of evolution are the …

Data scientists have built advanced algorithms using neural network models to gather
insights from big data. As a result, many novel deep-learning networks are being introduced …