Discovery of Dynamics Using Linear Multistep Methods
Rachael T. Keller, Qiang Du
Abstract
Related DatabasesWeb of Science You must be logged in with an active subscription to view this.Article DataHistorySubmitted: 30 December 2019Accepted: 20 October 2020Published online: 18 February 2021Keywordsdiscovery of dynamics, data-driven modeling, linear multistep methods, stability and convergence, root condition, learning dynamics, artificial intelligenceAMS Subject Headings65L06, 65L09, 65L20, 65P99, 68T99Publication DataISSN (print): 0036-1429ISSN (online): 1095-7170Publisher: Society for Industrial and Applied MathematicsCODEN: sjnaam
Topics & Concepts
Convergence (economics)Dynamics (music)MathematicsLinear multistep methodStability (learning theory)Applied mathematicsComputer scienceMathematical analysisMachine learningDifferential equationOrdinary differential equationDifferential algebraic equationEconomicsAcousticsPhysicsEconomic growthModel Reduction and Neural NetworksProbabilistic and Robust Engineering DesignControl Systems and Identification