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A framework for qualitative and semi-quantitative analysis in engineering design and evaluation Gedig, Michael H.
Abstract
A framework is presented which is used to support engineering decision-making in the presence of incomplete and imprecise information. A number of sound reasoning techniques which utilize this framework are described. These techniques include qualitative reasoning, a branch of study in the field of artificial intelligence, and semi-quantitative reasoning, which draws inferences from partially-specified numeric values. The constraint-satisfaction paradigm plays an important role in the implementation of these reasoning strategies. The notion of the constraint is well-suited to engineering planning and design, where projects are generally formulated in terms of a set of functional specifications. A computer program was developed based on the framework presented here. The program implements several complementary qualitative and semi-quantitative reasoning strategies. The specific techniques used in the program include constraint-satisfaction algorithms for both qualitative and numeric domains, interval arithmetic, and constraint inference methods. It was intended that the computer program developed as a part of this research serve as a practical tool which could provide logical justification for engineering decisions. For this reason, the program was developed on a platform which is both accessible and familiar. As part of the program, a convenient method of systematically specifying constraints was created, which mirrors the way in which engineering problems are normally specified. Examples are given which illustrate the application of the techniques presented here. These examples show that the techniques discussed in this thesis have significant potential for justifying engineering decisions made under conditions of uncertainty.
Item Metadata
Title |
A framework for qualitative and semi-quantitative analysis in engineering design and evaluation
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
1995
|
Description |
A framework is presented which is used to support engineering decision-making in the presence of incomplete
and imprecise information. A number of sound reasoning techniques which utilize this framework are
described. These techniques include qualitative reasoning, a branch of study in the field of artificial
intelligence, and semi-quantitative reasoning, which draws inferences from partially-specified numeric values.
The constraint-satisfaction paradigm plays an important role in the implementation of these reasoning
strategies. The notion of the constraint is well-suited to engineering planning and design, where projects are
generally formulated in terms of a set of functional specifications.
A computer program was developed based on the framework presented here. The program implements several
complementary qualitative and semi-quantitative reasoning strategies. The specific techniques used in the
program include constraint-satisfaction algorithms for both qualitative and numeric domains, interval
arithmetic, and constraint inference methods.
It was intended that the computer program developed as a part of this research serve as a practical tool which
could provide logical justification for engineering decisions. For this reason, the program was developed on a
platform which is both accessible and familiar. As part of the program, a convenient method of systematically
specifying constraints was created, which mirrors the way in which engineering problems are normally
specified. Examples are given which illustrate the application of the techniques presented here. These
examples show that the techniques discussed in this thesis have significant potential for justifying engineering
decisions made under conditions of uncertainty.
|
Extent |
5003795 bytes
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Genre | |
Type | |
File Format |
application/pdf
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Language |
eng
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Date Available |
2009-02-03
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Provider |
Vancouver : University of British Columbia Library
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Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
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DOI |
10.14288/1.0062468
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
1995-11
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Campus | |
Scholarly Level |
Graduate
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Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.