Inverse Engineering: A Machine Learning Approach to Support Engineering Synthesis

This research presents a knowledge processing methodology called inverse engineering, that uses machine learning techniques for early stage design in parameterized domains. This methodology functions as a model translator, changing the representation of analysis knowledge embedded in a unidirectional simulator, into a multidirectional model that supports design synthesis. This methodology requires addressing two issues.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Rao, R. Bharat

Contributors dc:contributor

• Lu, Stephen C-Y

• Engineering, Electronics and Electrical
• Artificial Intelligence
• Computer Science

Identifier

(UMI)AAI9329142

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/72004