Neural Computing and Applications

Abstract Analyzing chaotic dynamical systems is a challenging task, due to their strong sensitivity to initial conditions, implying that even the smallest deviation in the initial conditions will amplify exponentially over the time. As a result, the reconstruction of periodic or chaotic orbits of chaotic dynamical systems from time series represents a formidable task. In this paper, we consider t…

Abstract Battery management systems (BMSs) are essential for accessing and managing battery performance information, with state of health (SOH) estimation providing insights into the battery’s life expectancy. Electrochemical impedance spectroscopy (EIS) is a non-destructive method for SOH assessment. However, collecting EIS data across diverse operating conditions and battery types is both time-…

The reactivation of geological faults can be triggered by stress changes due to fluid injection affecting their permeability and potentially transforming them into preferential flow channels. This can impact reservoir production dynamics and compromise fluid storage safety. This study assesses the feasibility of long-term CO2 storage in a geological reservoir in the Campos Basin, Rio de Janeiro, …

Abstract Generative Adversarial Networks (GANs) are increasingly used in biometric systems. However, existing signature studies predominantly focus on strengthening discriminators or producing data for augmentation, leaving the quality and spoofing capability of generated forgeries insufficiently examined. To address this research gap, we propose Block-Induced Signature GAN (BISGAN )—a generator-…