Learnable Evolution Model in Engineering Design- GMU Machine Learning and Inference Laboratory

learnable evolution model in engineering design

(Michalski, Kaufman, Wojtusiak)

This project is concerned with the theoretical and methodological aspects of applying the Larnable Evolution Model (LEM) to the problems of engineering design. LEM appears to be particularly attractive for application to this area because it can significantly reduce the evolution/search length needed to find a desirable solution.

Based on the ideas of LEM, International Intelligent Systems, Inc., in collaboration with the National Institute of Standards and Technology and the Machine Learning and Inference Laboratory, has developed two systems for designing optimized heat exchangers in air conditioning systems:

- ISHED, for designing optimized evaporators
- ISCOD, for designing optimized condensers

The results have been highly promising, and indicate that the LEM-based design methodology may bring new, powerful tools to complex engineering design.

For references, seeĀ publications section.

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