Abstract State-of-health (SOH) estimation of lithium-ion batteries is crucial for ensuring the
reliability and safety of battery operation while keeping maintenance and service costs down …

In the present systematic review we identified and summarised current research activities in
the field of time series forecasting and imputation with the help of generative adversarial …

Reservoir level control in hydroelectric power plants has importance for the stability of the
electric power supply over time and can be used for flood control. In this sense, this paper …

Abstract Machine learning mechanism is establishing itself as a promising area for
modelling and forecasting complex time series over conventional statistical models. In this …

Insulators installed outdoors are vulnerable to the accumulation of contaminants on their
surface, which raise their conductivity and increase leakage current until a flashover occurs …

Safety and reliability are crucial for the next-generation supercapacitors used in energy
storage systems, while accurate prediction of the degradation trajectory and remaining …

Stock market prices are known to be very volatile and noisy, and their accurate forecasting is
a challenging problem. Traditionally, both linear and non-linear methods (such as ARIMA …

Multivariate time series forecasting has long been a research hotspot because of its wide
range of application scenarios. However, the dynamics and multiple patterns of …

Airborne pollen can trigger allergic rhinitis and other respiratory diseases in the synthesised
population, which makes it one of the most relevant biological contaminants. Therefore …

Abstract Generative Adversarial Networks (GANs) are one of the most significant research
directions in the field of Deep Learning (DL). GANs has received wide attention due to their …