Optimizing integrated systems with fuzzy logic and neural networks to reduce emissions and increase efficiency in residential buildings
- ETB/CETC/ACT, Nepean, Ontario (Canada)
In recent years, artificial intelligence (AI) has gained popularity, primarily through its application in consumer electronics. Control strategies based on fuzzy logic and neural networks generally perform better than conventional controls in complex environments with nonlinearities and correlations across input signals. At the same time, the strategy allows continuous control of the outputs depending on the inputs, yet always providing optimal points of operation. Combining residential space and water heating with one energy generating unit provides the potential for reduced capital cost, improved efficiency, reduced emissions and enhanced comfort. However, this potential has not been achieved to date, often because of the conflicting and complex interrelationship between the different factors. This paper will illustrate how AI can be applied to sets of residential integrated systems which could result in energy savings and reduced emissions.
- OSTI ID:
- 351701
- Report Number(s):
- CONF-970677-; TRN: IM9927%%226
- Resource Relation:
- Conference: 90. annual meeting and exhibition of the Air and Waste Management Association, Toronto (Canada), 8-13 Jun 1997; Other Information: PBD: 1997; Related Information: Is Part Of 1997 proceedings of the Air and Waste Management Association`s 90. annual meeting and exhibition; PB: [7000] p.
- Country of Publication:
- United States
- Language:
- English
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