Creating and Using Models for Engineering Design: A Machine-Learning Approach

Authors:
Sudhakar Yerramareddy;David K. Tcheng;Stephen C.-Y. Lu;Dennis N. Assanis
Affiliations:
-;-;-;-
Venue:
IEEE Expert: Intelligent Systems and Their Applications
Year:
1992

Citing 1
Cited 1

Induction of Decision Trees

Machine Learning

Fuzzy graph based metamodeling

WSC '96 Proceedings of the 28th conference on Winter simulation

Quantified Score

Hi-index	0.00

Visualization

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.