Title :
Creating and using models for engineering design: a machine-learning approach
Author :
Yerramareddy, Sudhakar ; Tcheng, David K. ; Lu, Stephen C-Y ; Assanis, Dennis N.
Author_Institution :
Illinois Univ., Urbana, IL, USA
fDate :
6/1/1992 12:00:00 AM
Abstract :
An adaptive and interactive modeling system (AIMS) that integrates simulation, optimization and machine learning to help engineers make design decisions is described. AIMS views engineering decision making as a two-phase process of creating and then using models. The competitive relation learner and the induce-and-select optimizer, AIMS´s two main components, and their roles in both phases of decision-making are discussed. AIMS´s role in supporting the design of a diesel engine that outputs power within the 440- to 460-kW range and consumes the least amount of fuel is also discussed.<>
Keywords :
CAD; decision support systems; interactive systems; internal combustion engines; learning systems; power engineering computing; 440 to 460 KW; AIMS; competitive relation learner; design decisions; diesel engine; engineering decision making; fuel; induce-and-select optimizer; interactive modeling system; machine learning; machine-learning approach; optimization; power; simulation; two-phase process; Adaptive systems; Availability; Databases; Design engineering; Design optimization; Expert systems; Learning systems; Machine learning; Machine learning algorithms; Power system modeling;
Journal_Title :
IEEE Expert
