2026-09-19T04:30:43Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/325122022-01-13T07:54:36Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Leon R. Glicksman.
Lehar, Matthew A., 1977-
Massachusetts Institute of Technology. Dept. of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2006-03-29T18:51:25Z
2006-03-29T18:51:25Z
2005
2005
http://hdl.handle.net/1721.1/32512
62074856
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.
Includes bibliographical references (p. 109-110).
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.
by Matthew A. Lehar.
Ph.D.
110 p.
4752218 bytes
4758364 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
A branching fuzzy-logic classifier for building optimization
Thesis
application/pdf
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unknown
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