Data-driven prediction in dynamical systems: recent developments
A Ghadami, BI Epureanu - Philosophical Transactions of …, 2022 - royalsocietypublishing.org
In recent years, we have witnessed a significant shift toward ever-more complex and ever-
larger-scale systems in the majority of the grand societal challenges tackled in applied …
larger-scale systems in the majority of the grand societal challenges tackled in applied …
Human movement variability, nonlinear dynamics, and pathology: is there a connection?
N Stergiou, LM Decker - Human movement science, 2011 - Elsevier
Fields studying movement generation, including robotics, psychology, cognitive science,
and neuroscience utilize concepts and tools related to the pervasiveness of variability in …
and neuroscience utilize concepts and tools related to the pervasiveness of variability in …
Root mean square error or mean absolute error? Use their ratio as well
DSK Karunasingha - Information Sciences, 2022 - Elsevier
The key statistical properties of the Root Mean Square Error (RMSE) and the Mean Absolute
Error (MAE) estimators were derived in this study for zero mean symmetric error …
Error (MAE) estimators were derived in this study for zero mean symmetric error …
Backpropagation algorithms and reservoir computing in recurrent neural networks for the forecasting of complex spatiotemporal dynamics
We examine the efficiency of Recurrent Neural Networks in forecasting the spatiotemporal
dynamics of high dimensional and reduced order complex systems using Reservoir …
dynamics of high dimensional and reduced order complex systems using Reservoir …
[HTML][HTML] Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data
We use recent advances in the machine learning area known as “reservoir computing” to
formulate a method for model-free estimation from data of the Lyapunov exponents of a …
formulate a method for model-free estimation from data of the Lyapunov exponents of a …
Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network
Accurate estimation of the remaining useful life of lithium-ion batteries is critically important
for electronic devices. In the existing literature, the widely applied model-based approaches …
for electronic devices. In the existing literature, the widely applied model-based approaches …
Nonlinear time-series analysis revisited
E Bradley, H Kantz - Chaos: An Interdisciplinary Journal of Nonlinear …, 2015 - pubs.aip.org
In 1980 and 1981, two pioneering papers laid the foundation for what became known as
nonlinear time-series analysis: the analysis of observed data—typically univariate—via …
nonlinear time-series analysis: the analysis of observed data—typically univariate—via …
Topological data analysis of financial time series: Landscapes of crashes
We explore the evolution of daily returns of four major US stock market indices during the
technology crash of 2000, and the financial crisis of 2007–2009. Our methodology is based …
technology crash of 2000, and the financial crisis of 2007–2009. Our methodology is based …
Synchronization
抄録< jats: p> First recognized in 1665 by Christiaan Huygens, synchronization phenomena
are abundant in science, nature, engineering and social life. Systems as diverse as clocks …
are abundant in science, nature, engineering and social life. Systems as diverse as clocks …
[图书][B] Nonlinear time series analysis
H Kantz, T Schreiber - 2003 - books.google.com
The paradigm of deterministic chaos has influenced thinking in many fields of science.
Chaotic systems show rich and surprising mathematical structures. In the applied sciences …
Chaotic systems show rich and surprising mathematical structures. In the applied sciences …