TY - GEN
T1 - Generating a fuzzy logic system from optimized numerical models
AU - Ari, S.
AU - Khalifa, H. E.
AU - Dannenhoffer, J. F.
AU - Wilcoxen, P.
AU - Isik, C.
PY - 2007
Y1 - 2007
N2 - This paper presents a novel approach to the optimization of a system using soft computing. In many instances optimum solutions to complex problems can be calculated using analytic or numeric approaches, but with significant barriers for practical use, such as computational complexity, sensitivity to parameter variations, and necessity to use many measured variables. In this study, a traditional optimization method is used to calculate off-line optimum solutions to an indoor environmental control problem at numerous operating points. These solutions are, in turn, used as exemplars to train an intelligent system such as a fuzzy logic system or a neural network, resulting in a control system whose behavior exhibits the desirable features of the family of optimum solutions. It has been shown that this methodology (named Modeled Optimized System - MOS) results in a controller for an indoor environmental system, which improves occupant satisfaction, saves energy, and can be implemented in a practical fashion.
AB - This paper presents a novel approach to the optimization of a system using soft computing. In many instances optimum solutions to complex problems can be calculated using analytic or numeric approaches, but with significant barriers for practical use, such as computational complexity, sensitivity to parameter variations, and necessity to use many measured variables. In this study, a traditional optimization method is used to calculate off-line optimum solutions to an indoor environmental control problem at numerous operating points. These solutions are, in turn, used as exemplars to train an intelligent system such as a fuzzy logic system or a neural network, resulting in a control system whose behavior exhibits the desirable features of the family of optimum solutions. It has been shown that this methodology (named Modeled Optimized System - MOS) results in a controller for an indoor environmental system, which improves occupant satisfaction, saves energy, and can be implemented in a practical fashion.
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U2 - 10.1109/NAFIPS.2007.383882
DO - 10.1109/NAFIPS.2007.383882
M3 - Conference contribution
AN - SCOPUS:35148883036
SN - 1424412145
SN - 9781424412143
T3 - Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS
SP - 452
EP - 457
BT - NAFIPS 2007
T2 - NAFIPS 2007: 2007 Annual Meeting of the North American Fuzzy Information Processing Society
Y2 - 24 June 2007 through 27 June 2007
ER -