Abstract
For several years researchers at the JCEM have sought ways to apply various artificial intelligence methods to commercial building HVAC operations. This paper, based on two earlier articles, reports on some of the key results of work at Colorado. Expert system enhanced with neural networks trained by historical building data appear to be particularly promising for efficient and semi-automatic supervision of HVAC systems for commercial buildings. It appears that the over reliance on logic associated with expert systems alone can be reduced with a bettwe results neurl networks.
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