國立虎尾科技大學 |

Surrogate Model-Based Engineering Design and Optimization

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Surrogate Model-Based Engineering Design and Optimization/ by Ping Jiang, Qi Zhou, Xinyu Shao.
作者:	Jiang, Ping.
其他作者:	Shao, Xinyu.
面頁冊數:	IX, 240 p. 99 illus., 72 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Manufacturing, Machines, Tools, Processes. -
電子資源:	https://doi.org/10.1007/978-981-15-0731-1
ISBN:	9789811507311

Surrogate Model-Based Engineering Design and Optimization
Jiang, Ping.

Surrogate Model-Based Engineering Design and Optimization[electronic resource] /by Ping Jiang, Qi Zhou, Xinyu Shao. - 1st ed. 2020. - IX, 240 p. 99 illus., 72 illus. in color.online resource. - Springer Tracts in Mechanical Engineering,2195-9862. - Springer Tracts in Mechanical Engineering,.

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.

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.

ISBN: 9789811507311

Standard No.: 10.1007/978-981-15-0731-1doiSubjects--Topical Terms:

1226012
Manufacturing, Machines, Tools, Processes.

LC Class. No.: TA174

Dewey Class. No.: 620.0042

Surrogate Model-Based Engineering Design and Optimization
LDR:02808nam a22004215i 4500 001 1026073
003 DE-He213
005 20200706143417.0
007 cr nn 008mamaa
008 210318s2020 si | s |||| 0|eng d
020 $a 9789811507311 $9 978-981-15-0731-1
024 7 $a 10.1007/978-981-15-0731-1 $2 doi
035 $a 978-981-15-0731-1
050 4 $a TA174
050 4 $a TA403.6
072 7 $a TBD $2 bicssc
072 7 $a TEC016020 $2 bisacsh
072 7 $a TBD $2 thema
082 0 4 $a 620.0042 $2 23
100 1 $a Jiang, Ping. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1322365
245 1 0 $a Surrogate Model-Based Engineering Design and Optimization $h [electronic resource] / $c by Ping Jiang, Qi Zhou, Xinyu Shao.
250 $a 1st ed. 2020.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a IX, 240 p. 99 illus., 72 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Springer Tracts in Mechanical Engineering, $x 2195-9862
505 0 $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.
520 $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.
650 2 4 $a Manufacturing, Machines, Tools, Processes. $3 1226012
650 2 4 $a Engineering Mathematics. $3 1203947
650 1 4 $a Engineering Design. $3 670857
650 0 $a Manufactures. $3 680602
650 0 $a Engineering mathematics. $3 562757
650 0 $a Engineering design. $3 560518
700 1 $a Shao, Xinyu. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1322367
700 1 $a Zhou, Qi. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1322366
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811507304
776 0 8 $i Printed edition: $z 9789811507328
776 0 8 $i Printed edition: $z 9789811507335
830 0 $a Springer Tracts in Mechanical Engineering, $x 2195-9862 $3 1253585
856 4 0 $u https://doi.org/10.1007/978-981-15-0731-1
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)