A branching fuzzy-logic classifier for building optimization
Name
62074856-MIT.pdf
Description
Full printable version
Size
7.99 MB
Format
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Checksum (MD5)
01357d30012b6b11b71ce12ffb74a3c9
Author(s)
Lehar, Matthew A., 1977-
Advisor(s)
Leon R. Glicksman.
Date Issued
2005
Publisher
Massachusetts Institute of Technology
Abstract
We present an input-output model that learns to emulate a complex building simulation of high dimensionality. Many multi-dimensional systems are dominated by the behavior of a small number of inputs over a limited range of input variation. Some also exhibit a tendency to respond relatively strongly to certain inputs over small ranges, and to other inputs over very large ranges of input variation. A branching linear discriminant can be used to isolate regions of local linearity in the input space, while also capturing the effects of scale. The quality of the classification may be improved by using a fuzzy preference relation to classify input configurations that are not well handled by the linear discriminant.
Description
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.
Includes bibliographical references (p. 109-110).
Subjects
Mechanical Engineering.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
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