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University of Illinois at Urbana-Champaign

Automated symbolic model identification for nonlinear dynamical systems from time-series data with limited sampling frequency and precision

Abstract

dc:description

Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-12-01

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Nuclear, Plasma, Radiolgc Engr
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Zhou, Long
Contributors dc:contributor
  • Zhang, Yang
  • Huff, Kathryn D.
  • Bretl, Timothy Wolfe
  • Uddin, Rizwan

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • Copyright 2022 Long Zhou
Language dc:language
en, eng

Identifiers

dc:identifier.*
Handle dc:identifier
https://hdl.handle.net/2142/117539
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/117539

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Zhou, Long. Automated symbolic model identification for nonlinear dynamical systems from time-series data with limited sampling frequency and precision. Dissertation thesis, University of Illinois at Urbana-Champaign, 2022. https://hdl.handle.net/2142/117539