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dc.creatorYamaha, M.
dc.creatorTakahashi, M.
dc.date.accessioned2007-04-27T16:41:50Z
dc.date.available2007-04-27T16:41:50Z
dc.date.issued2004
dc.identifier.otherESL-IC-04-10-11
dc.identifier.urihttps://hdl.handle.net/1969.1/5035
dc.description.abstractAuthors tried to apply an Artificial Neural Network (ANN) to estimation of state of building systems. The systems used in this study were gas combustion water heaters. Empirical equations to estimate gas consumption from measureble properies such as exhaust gas temperature and electric current were obtained from experiments. Some operational modes, which were hot water supply, additional combustion to keep water temperature in bathtub, and anti-frozen heater for plumbing, were needed to be identified. Electric currents, temperature of supply water and exhaust gas had been measured as operational indices. ANN was applied to identify modes automatically using learning algorism. The modes were porperly identified and gas consumption was estimated in practical accuracy.en
dc.format.extent217892 bytesen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherEnergy Systems Laboratory (http://esl.tamu.edu)
dc.publisherTexas A&M University (http://www.tamu.edu)
dc.subjectdomestic hot wateren
dc.subjectartificial neural networken
dc.subjectenergyen
dc.titleAn Analysis Method for Operations of Hot Water Heaters by Artificial Neural Networksen


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