Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Advanced multiresponse process optim...
~
Majstorovic, Vidosav D.
Advanced multiresponse process optimisation = an intelligent and integrated approach /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Advanced multiresponse process optimisation/ by Tatjana V. Sibalija, Vidosav D. Majstorovic.
Reminder of title:
an intelligent and integrated approach /
Author:
Sibalija, Tatjana V.
other author:
Majstorovic, Vidosav D.
Published:
Cham :Springer International Publishing : : 2016.,
Description:
xvii, 284 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Manufacturing processes. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-19255-0
ISBN:
9783319192550
Advanced multiresponse process optimisation = an intelligent and integrated approach /
Sibalija, Tatjana V.
Advanced multiresponse process optimisation
an intelligent and integrated approach /[electronic resource] :by Tatjana V. Sibalija, Vidosav D. Majstorovic. - Cham :Springer International Publishing :2016. - xvii, 284 p. :ill. (some col.), digital ;24 cm.
Introduction -- Review of multiresponse optimisation approaches -- An intelligent, integrated, problem-independent method for multiresponse process optimisation -- Implementation of an intelligent, integrated, problem-independent method to multiresponse process optimisation -- Case studies -- Conclusion.
This book presents an intelligent, integrated, problem-independent method for multiresponse process optimization. In contrast to traditional approaches, the idea of this method is to provide a unique model for the optimization of various processes, without imposition of assumptions relating to the type of process, the type and number of process parameters and responses, or interdependences among them. The presented method for experimental design of processes with multiple correlated responses is composed of three modules: an expert system that selects the experimental plan based on the orthogonal arrays; the factor effects approach, which performs processing of experimental data based on Taguchi's quality loss function and multivariate statistical methods; and process modeling and optimization based on artificial neural networks and metaheuristic optimization algorithms. The implementation is demonstrated using four case studies relating to high-tech industries and advanced, non-conventional processes.
ISBN: 9783319192550
Standard No.: 10.1007/978-3-319-19255-0doiSubjects--Topical Terms:
564466
Manufacturing processes.
LC Class. No.: TS183
Dewey Class. No.: 670
Advanced multiresponse process optimisation = an intelligent and integrated approach /
LDR
:02311nam a2200313 a 4500
001
860163
003
DE-He213
005
20160712170843.0
006
m d
007
cr nn 008maaau
008
170720s2016 gw s 0 eng d
020
$a
9783319192550
$q
(electronic bk.)
020
$a
9783319192543
$q
(paper)
024
7
$a
10.1007/978-3-319-19255-0
$2
doi
035
$a
978-3-319-19255-0
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TS183
072
7
$a
TGXT
$2
bicssc
072
7
$a
TEC020000
$2
bisacsh
082
0 4
$a
670
$2
23
090
$a
TS183
$b
.S563 2016
100
1
$a
Sibalija, Tatjana V.
$3
1101622
245
1 0
$a
Advanced multiresponse process optimisation
$h
[electronic resource] :
$b
an intelligent and integrated approach /
$c
by Tatjana V. Sibalija, Vidosav D. Majstorovic.
260
$a
Cham :
$c
2016.
$b
Springer International Publishing :
$b
Imprint: Springer,
300
$a
xvii, 284 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
505
0
$a
Introduction -- Review of multiresponse optimisation approaches -- An intelligent, integrated, problem-independent method for multiresponse process optimisation -- Implementation of an intelligent, integrated, problem-independent method to multiresponse process optimisation -- Case studies -- Conclusion.
520
$a
This book presents an intelligent, integrated, problem-independent method for multiresponse process optimization. In contrast to traditional approaches, the idea of this method is to provide a unique model for the optimization of various processes, without imposition of assumptions relating to the type of process, the type and number of process parameters and responses, or interdependences among them. The presented method for experimental design of processes with multiple correlated responses is composed of three modules: an expert system that selects the experimental plan based on the orthogonal arrays; the factor effects approach, which performs processing of experimental data based on Taguchi's quality loss function and multivariate statistical methods; and process modeling and optimization based on artificial neural networks and metaheuristic optimization algorithms. The implementation is demonstrated using four case studies relating to high-tech industries and advanced, non-conventional processes.
650
0
$a
Manufacturing processes.
$3
564466
650
0
$a
Sustainable engineering.
$3
700213
650
1 4
$a
Engineering.
$3
561152
650
2 4
$a
Manufacturing, Machines, Tools.
$3
670281
650
2 4
$a
Artificial Intelligence (incl. Robotics)
$3
593924
650
2 4
$a
Robotics and Automation.
$3
782979
650
2 4
$a
Computational Intelligence.
$3
768837
650
2 4
$a
Operation Research/Decision Theory.
$3
881408
700
1
$a
Majstorovic, Vidosav D.
$3
1101623
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-19255-0
950
$a
Engineering (Springer-11647)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login