From the 2 of 6 linked papers with an AI index.
6 papers
High-fidelity inference of power grid frequency distributions
Alessandro Lonardi, Benjamin Schäfer, Christian Beck
The paper presents a statistical inference method that models power grid frequency fluctuations with a stochastic process, using maximum likelihood and superstatistics to accuratel…
Superstatistical Analysis of PDFs and autocorrelation functions for air pollution concentrations in the UK
Nisal Amarakoon, Hankun He, Christian Beck
The paper applies superstatistical methods from non‑equilibrium physics to model the probability distributions and autocorrelation of hourly air‑pollution measurements across the U…
Stochastic Modeling of Power-Grid Frequency Fluctuations in Low-Inertia Systems via a Gaussian-Core Potential and Superstatistics
Wanru Hao, Alessandro Lonardi, Christian Beck
Power grid frequency stability is fundamental to the secure operation of modern energy systems, yet the growing penetration of renewables and the associated reduction of system ine…
Understanding the complexity of frequency and phase angle fluctuations in power grids
Alessandro Lonardi, Jacques M. Maritz, Leonardo Rydin Gorjão +1
Power grids must modernize to meet climate goals while maintaining reliable and stable operating conditions. Yet progress is hindered by a limited understanding of the stochastic p…
Analyzing Spatio-Temporal Dynamics of Dissolved Oxygen for the River Thames using Superstatistical Methods and Machine Learning
Hankun He, Takuya Boehringer, Benjamin Schäfer +2
By employing superstatistical methods and machine learning, we analyze time series data of water quality indicators for the River Thames, with a specific focus on the dynamics of d…
Spatial analysis of tails of air pollution PDFs in Europe
Hankun He, Benjamin Schäfer, Christian Beck
Outdoor air pollution is estimated to cause a huge number of premature deaths worldwide, it catalyses many diseases on a variety of time scales, and it has a detrimental effect on…