nlin.CD · 2026-06-08 · No. 17
Chaotic Dynamics, 2026-06-08.
1 new papers in nlin.CD. Titles, authors,
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01 — The papers
1 entries-
01
Unified Geometry-Guided ML-FTLE for Tracking Transient Chaos from Scalar Time Series
S. V. Manivelan, Andrei Velichko, I. Manimehan
nlin.CD · cs.LG · physics.data-an
Detecting transient chaos from scalar observations without governing equations represents a fundamental challenge in nonlinear dynamics. We propose a geometry-guided machine learning framework that unifies predictive trajectory divergence with macroscopic attractor morphology to track abrupt regime shifts. The methodology extracts a local instability scale via out-of-sample k-nearest neighbor forecast errors to establish the ML-FTLE...
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