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on1126283742 |
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OCoLC |
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20241006213017.0 |
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cr cnu|||unuuu |
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191104s2020 si a ob 000 0 eng d |
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|a 9811507317
|q (electronic bk.)
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|z 9789811507304
|q (print)
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|z 9811507309
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|a 10.1007/978-981-15-0731-1
|2 doi
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|a 10.1007/978-981-15-0
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|a (OCoLC)1126283742
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|a com.springer.onix.9789811507311
|b Springer Nature
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|a HCDD
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100 |
1 |
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|a Jiang, Ping,
|e author.
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245 |
1 |
0 |
|a Surrogate model-based engineering design and optimization /
|c Ping Jiang, Qi Zhou, Xinyu Shao.
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264 |
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1 |
|a Singapore :
|b Springer,
|c 2020.
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300 |
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|a 1 online resource (ix, 240 pages) :
|b illustrations (some color)
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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490 |
1 |
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|a Springer tracts in mechanical engineering,
|x 2195-9862
|
504 |
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|a Includes bibliographical references.
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588 |
0 |
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|a Online resource; title from PDF title page (SpringerLink, viewed November 4, 2019).
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505 |
0 |
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|a Introduction -- Classic types of surrogate model -- Ensemble of surrogate models -- Multi-fidelity surrogate model -- Verification methods for surrogate model -- Sampling approaches -- Surrogate model-based design optimization -- Conclusions.
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520 |
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|a This book covers some of the most popular methods in design space sampling, ensembling surrogate models, multi-fidelity surrogate model construction, surrogate model selection and validation, surrogate-based robust design optimization, and surrogate-based evolutionary optimization. Surrogate or metamodels are now frequently used in complex engineering product design to replace expensive simulations or physical experiments. They are constructed from available input parameter values and the corresponding output performance or quantities of interest (QOIs) to provide predictions based on the fitted or interpolated mathematical relationships. The book highlights a range of methods for ensembling surrogate and multi-fidelity models, which offer a good balance between surrogate modeling accuracy and building cost. A number of real-world engineering design problems, such as three-dimensional aircraft design, are also provided to illustrate the ability of surrogates for supporting complex engineering design. Lastly, illustrative examples are included throughout to help explain the approaches in a more "hands-on" manner
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650 |
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|a Engineering design
|x Mathematical models.
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650 |
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7 |
|a Engineering design
|x Mathematical models
|2 fast
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700 |
1 |
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|a Zhou, Qi,
|e author.
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700 |
1 |
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|a Shao, Xinyu,
|e author.
|
758 |
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|i has work:
|a Surrogate Model-Based Engineering Design and Optimization (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCYRq3btMfCYD6DwmmmbBMX
|4 https://id.oclc.org/worldcat/ontology/hasWork
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776 |
0 |
8 |
|i Print version:
|z 9811507309
|z 9789811507304
|w (OCoLC)1117632240
|
830 |
|
0 |
|a Springer tracts in mechanical engineering,
|x 2195-9862
|
856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-981-15-0731-1
|y Click for online access
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903 |
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|a SPRING-ENGINE2020
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994 |
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|a 92
|b HCD
|