LEADER 04270nam  22007815  450 
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010   $a9783319192550
010   $a3319192558
024 7 $a10.1007/978-3-319-19255-0
035   $a(CKB)3710000000452181
035   $a(EBL)3567960
035   $a(SSID)ssj0001534586
035   $a(PQKBManifestationID)11855993
035   $a(PQKBTitleCode)TC0001534586
035   $a(PQKBWorkID)11498108
035   $a(PQKB)10484663
035   $a(DE-He213)978-3-319-19255-0
035   $a(MiAaPQ)EBC3567960
035   $a(PPN)187685185
035   $a(EXLCZ)993710000000452181
100   $a20150725d2016      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aAdvanced Multiresponse Process Optimisation $eAn Intelligent and Integrated Approach /$fby Tatjana V. ?ibalija, Vidosav D. Majstorovi?
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (309 p.)
300   $aDescription based upon print version of record.
311 08$a9783319192543 
311 08$a331919254X 
320   $aIncludes bibliographical references.
327   $aIntroduction -- 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.
330   $aThis 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.
606   $aManufactures
606   $aArtificial intelligence
606   $aRobotics
606   $aAutomation
606   $aComputational intelligence
606   $aOperations research
606   $aDecision making
606   $aManufacturing, Machines, Tools, Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/T22050
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aRobotics and Automation$3https://scigraph.springernature.com/ontologies/product-market-codes/T19020
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aOperations Research/Decision Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/521000
615  0$aManufactures.
615  0$aArtificial intelligence.
615  0$aRobotics.
615  0$aAutomation.
615  0$aComputational intelligence.
615  0$aOperations research.
615  0$aDecision making.
615 14$aManufacturing, Machines, Tools, Processes.
615 24$aArtificial Intelligence.
615 24$aRobotics and Automation.
615 24$aComputational Intelligence.
615 24$aOperations Research/Decision Theory.
676   $a620
700   $a?ibalija$b Tatjana V$4aut$4http://id.loc.gov/vocabulary/relators/aut$0760815
702   $aMajstorovi?$b Vidosav D$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910254194003321
996   $aAdvanced Multiresponse Process Optimisation$92514057
997   $aUNINA