| Tag |
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| LEADER |
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| 001 |
in00002780122 |
| 005 |
20150922143038.0 |
| 006 |
m fo d |
| 007 |
cr unu|||||||| |
| 008 |
121114s2012 txu obm 000 0 eng d |
| 035 |
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|a (OCoLC)ocn817975432
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| 035 |
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|a (OCoLC)817975432
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| 035 |
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|a (TxCM)http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11783
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| 040 |
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|a TXA
|c TXA
|d UtOrBLW
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| 049 |
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|a TXAM
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| 099 |
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|a 2012
|a Thesis
|a 1969.1/ETD-TAMU-2012-08-11783
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| 100 |
1 |
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|a Galvan, Edgar.
|
| 245 |
1 |
2 |
|a A genetic algorithm approach for technology characterization /
|c by Edgar Galvan.
|
| 264 |
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1 |
|a [College Station, Tex.] :
|b [Texas A&M University],
|c [2012]
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| 300 |
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|a 1 online resource.
|
| 336 |
|
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|a text
|b txt
|2 rdacontent
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| 337 |
|
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|a computer
|b c
|2 rdamedia
|
| 338 |
|
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|a online resource
|b cr
|2 rdacarrier
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| 500 |
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|a "Major Subject: Mechanical Engineering"
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| 588 |
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|a Description from author supplied metadata (automated record created 2012-10-22 13:24:58).
|
| 502 |
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|b Master of Science
|c Texas A&M University
|d 2012
|o http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11783
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| 504 |
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|a Includes bibliographical references.
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| 516 |
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|a Text (Thesis)
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| 520 |
3 |
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|a It is important for engineers to understand the capabilities and limitations of the technologies they consider for use in their systems. Several researchers have investigated approaches for modeling the capabilities of a technology with the aim of supporting the design process. In these works, the information about the physical form is typically abstracted away. However, the efficient generation of an accurate model of technical capabilities remains a challenge. Pareto frontier based methods are often used but yield results that are of limited use for subsequent decision making and analysis. Models based on parameterized Pareto frontiers--termed Technology Characterization Models (TCMs)--are much more reusable and composable. However, there exists no efficient technique for modeling the parameterized Pareto frontier. The contribution of this thesis is a new algorithm for modeling the parameterized Pareto frontier to be used as a model of the characteristics of a technology. The novelty of the algorithm lies in a new concept termed predicted dominance. The proposed algorithm uses fundamental concepts from multi-objective optimization and machine learning to generate a model of the technology frontier.
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| 500 |
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|a Electronic resource.
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| 650 |
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4 |
|a Major Mechanical Engineering.
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| 653 |
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|a Capability model
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| 653 |
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|a nondominated frontier
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| 653 |
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|a Genetic Algorithm
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| 700 |
1 |
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|a Malak, Richard J.,
|e thesis advisor.
|
| 856 |
4 |
0 |
|u http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11783
|z Link to OAK Trust copy
|t 0
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| 994 |
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|a C0
|b TXA
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| 948 |
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|a cataloged
|b h
|c 2012/11/14
|d o
|e blrosas
|f 1:35:40 pm
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| 999 |
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|a MARS
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| 999 |
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f |
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|i c223eeca-90cd-31ff-bb15-e85ed5c718d5
|t 0
|
| 952 |
f |
f |
|a Texas A&M University
|b College Station
|c Electronic Resources
|d Available Online
|t 0
|e 2012 Thesis 1969.1/ETD-TAMU-2012-08-11783
|h Other scheme
|
| 998 |
f |
f |
|a 2012 Thesis 1969.1/ETD-TAMU-2012-08-11783
|t 0
|l Available Online
|