Accession Number:

AD1104379

Title:

Surviving the Data Deluge: A Combined Dynamical Systems/Machine Learning Approach

Descriptive Note:

Technical Report,01 Sep 2015,31 Aug 2019

Corporate Author:

NORTHEASTERN UNIVERSITY Boston United States

Personal Author(s):

Report Date:

2020-06-25

Pagination or Media Count:

42.0

Abstract:

This research sought to develop a comprehensive, computationally tractable framework for synthesizing information driven systems capable of both autonomously operating and supporting safety--critical human operations in rapidly changing data deluged scenarios. Its conceptual backbone was a rigorous integration of systems theory, machine learning and optimization elements that emphasized robustness, computational simplicity and improved situational awareness. The research advanced the state of the art in systems theory by developing a tractable framework for robust identificationmodel invalidation of a broad class of dynamical systems that incorporates ideas from machine learning and semi-algebraic optimization to handle outliers, missing data and substantial noise levels.

Subject Categories:

  • Human Factors Engineering and Man Machine Systems
  • Information Science

Distribution Statement:

APPROVED FOR PUBLIC RELEASE