publication . Doctoral thesis . 2014

Automated Feature Design for Time Series Classification by Genetic Programming

Harvey, Dustin Yewell;
Open Access
  • Published: 01 Jan 2014
  • Publisher: eScholarship, University of California
  • Country: United States
Abstract
Time series classification (TSC) methods discover and exploit patterns in time series and other one-dimensional signals. Although many accurate, robust classifiers exist for multivariate feature sets, general approaches are needed to extend machine learning techniques to make use of signal inputs. Numerous applications of TSC can be found in structural engineering, especially in the areas of structural health monitoring and non-destructive evaluation. Additionally, the fields of process control, medicine, data analytics, econometrics, image and facial recognition, and robotics include TSC problems. This dissertation details, demonstrates, and evaluates Autofead,...
Subjects
free text keywords: UCSD Dissertations, Academic Structural Engineering. (Discipline)
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