Fuzzy logic and neural network approximation to indoor comfort and energy optimization

S. Ari, H. E. Khalifa, J. F. Dannenhoffer, P. Wilcoxen, C. Isik

Research output: Chapter in Book/Entry/PoemConference contribution

10 Scopus citations

Abstract

Research about indoor environmental satisfaction has indicated that allowing building occupants to adjust their local environment to their preferences increases thermal satisfaction and human performance at the workplace. However, such systems have been considered as a reason of possible increase in energy consumption of environmental control systems. In our previous study [1], we minimized the energy consumption of distributed environmental control systems without increasing occupant thermal dissatisfaction using gradient-based optimization. We then approximated the optimal models using fuzzy systems based on the nearest neighbors. Those fuzzy models were specific to different outside temperatures. This required a considerable storage space to keep all the fuzzy rules of each outside temperature. In this study, we generated a fuzzy system and a neural network system, which are generated for any outside temperature. Our results show these two models approximate the results of gradient-based optimization in a practically feasible fashion.

Original languageEnglish (US)
Title of host publicationAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
Pages692-695
Number of pages4
DOIs
StatePublished - 2006
EventNAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society - Montreal, QC, Canada
Duration: Jun 3 2006Jun 6 2006

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Other

OtherNAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society
Country/TerritoryCanada
CityMontreal, QC
Period6/3/066/6/06

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

Fingerprint

Dive into the research topics of 'Fuzzy logic and neural network approximation to indoor comfort and energy optimization'. Together they form a unique fingerprint.

Cite this