Data of "Deep Learning for Chaos Detection"

Published: 14 July 2023| Version 3 | DOI: 10.17632/k4x675k5dm.3
Contributors:
Roberto Barrio,
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Description

In this folder there are files that contain the raw material and the filtered data used for the training and test of the networks used in the paper "Deep Learning for Chaos Detection". Namely, those starting with LM or Logistic_Map corresponds to the Logistic Map and those with LS and Lorenz_System corresponds to the Lorenz System. The files marked with Dataset in the name are the raw data (time series and Lyapunov exponents) computed as presented in the paper. And those marked with TEST, VALIDATION and TRAIN are the curated data given to the ML systems. In the case of the Lorenz System the data is already normalized as described in the paper. Logistic Map: All files are ordered as follows Initial condition, parameter a, first Lyapunov exponent, time series Lorenz System: All files are ordered as follows except LS_3D.txt Initial conditions, parameters σ; r; b, first Lyapunov exponent, time series x(t); y(t); z(t); x(t+1); y(t+1); z(t+1) Each line of LS_3D.txt contains parameters σ; r; b, and then 0 o 1 depending on whether it is regular or chaotic.

Files

Institutions

Universidad de Zaragoza

Categories

Chaos Theory, Machine Learning

Licence