Balıkesir Üniversitesi
Kütüphane ve Dokümantasyon Daire Başkanlığı

Advanced multiresponse process optimisation: (Kayıt no. 37864)

MARC ayrıntıları
000 -LEADER
fixed length control field 03919nam a2200265 i 4500
001 - CONTROL NUMBER
control field 41260
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160216s2015||||||| |||||||||||eng|d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783319192550
Qualifying information (hardback).
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)914706234
040 ## - CATALOGING SOURCE
Original cataloging agency AU-PeEL
Language of cataloging eng
Transcribing agency AU-PeEL
Modifying agency AU-PeEL
-- BAUN
Description conventions rda
049 ## - LOCAL HOLDINGS (OCLC)
Holding library BAUN_MERKEZ
050 14 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TS183
Item number .S53 2016
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Sibalija, Tatjana V.
245 10 - TITLE STATEMENT
Title Advanced multiresponse process optimisation:
Remainder of title an intelligent and integrated approach /
Statement of responsibility, etc Tatjana V Sibalija.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cham :
Name of producer, publisher, distributor, manufacturer Springer International Publishing,
Date of production, publication, distribution, manufacture, or copyright notice 2015.
300 ## - PHYSICAL DESCRIPTION
Extent 309 pages :
Other physical details illustrations (some color) ;
Dimensions 26 cm.
336 ## - CONTENT TYPE
Source rdacontent
Content Type Term text
Content Type Code txt
337 ## - MEDIA TYPE
Source rdamedia
Media Type Term unmediated
Media Type Code unmediated
338 ## - CARRIER TYPE
Source rdacarrier
Carrier Type Term volume
Carrier Type Code object
505 00 - FORMATTED CONTENTS NOTE
Title Foreword
-- -- Preface
-- -- Acknowledgments
-- -- Contents
-- -- Abbreviations and Symbols
-- -- 1 Introduction
-- -- Abstract
-- -- 1.1 Process Optimisation Based on Experimental Design
-- -- 1.1.1 Foundations of Taguchi's Method
-- -- 1.1.1.1 Orthogonal Arrays
-- -- 1.1.1.2 Robustness
-- -- 1.1.1.3 Quality Loss Function
-- -- 1.2 The Need for Advanced Multiresponse Process Optimisation in a Modern Industry
-- -- References
-- -- 2 Review of Multiresponse Process Optimisation Methods
-- -- Abstract
-- -- 2.1 Conventional Multiresponse Process Optimisation Approaches Based on Statistical Methods
-- -- 2.1.1 Response Surface Methodology.
-- -- 2.1.2 Taguchi's Robust Parameter Design
-- -- 2.1.2.1 Multiresponse Optimisation Based on Engineering Experience and Knowledge About the Process in Taguchi Method
-- -- 2.1.2.2 Multiresponse Optimisation Based on the Assignment of Weigh Factors to Process Responses in Taguchi Method
-- -- 2.1.2.3 Multiresponse Optimisation Based on Regression Analysis in Taguchi Method
-- -- 2.1.2.4 Multiresponse Optimisation Based on Desirability Function Analysis in Taguchi Method
-- -- 2.1.2.5 Multiresponse Optimisation Based on Data Envelopment Analysis in Taguchi Method.
-- --2.1.2.6 Multiresponse Optimisation Based on Principal Component Analysis in Taguchi Method
-- -- 2.1.2.7 Multiresponse Optimisation Based on Grey Relational Analysis in Taguchi Method
-- -- 2.1.2.8 Other Conventional Multiresponse Optimisation Approaches
-- -- 2.1.3 Multiresponse Optimisation Based on Goal-Programming
-- -- 2.2 Non-conventional Multiresponse Process Optimisation Approaches Based on Artificial Intelligence Techniques
-- -- 2.2.1 Multiresponse Optimisation Based on Fuzzy Multi-attribute Decision Making and Fuzzy Logic
-- -- 2.2.2 Multiresponse Optimisation Based on Artificial Neural Networks.
-- -- 2.2.3 Multiresponse Optimisation Based on Metaheuristic Search Techniques
-- -- 2.2.3.1 Multiresponse Optimisation Based on Genetic Algorithm
-- -- 2.2.3.2 Multiresponse Optimisation Based on Simulated Annealing
-- -- 2.2.3.3 Multiresponse Optimisation Based on Particle Swarm Optimisation
-- -- 2.2.3.4 Multiresponse Optimisation Based on Ant Colony Optimisation
-- -- 2.2.3.5 Multiresponse Optimisation Based on Tabu Search
-- -- 2.2.3.6 Multiresponse Optimisation Based on Recently Developed Evolutionary Algorithms
-- -- Multiresponse Optimisation Based on Artificial Bee Colony Algorithm.
-- -- Multiresponse Optimisation Based on Biogeography-Based Optimisation
-- -- Multiresponse Optimisation Based on Teaching--Learning-Based Optimisation
-- -- 2.2.4 Multiresponse Optimisation Using Expert System
-- -- References
-- -- 3 An Intelligent, Integrated, Problem-Independent Method for Multiresponse Process Optimisation
-- -- Abstract
-- -- 3.1 Method Overview: Intelligent System for Multiresponse Robust Process Design (IS-MR-RPD) Model
-- -- 3.2 Design of Experimental Plan
-- -- 3.2.1 Taguchi's Experimental Design: Orthogonal Arrays
-- -- 3.2.2 Expert System for the Design of Experiment (ES_DoE) in IS-MR-RPD Model.
-- --3.2.2.1 Expert System Shell Java DON.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Expert systems (Computer science)
9 (RLIN) 53363
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Majstorović, Vidosav D.
9 (RLIN) 101774
Relator term Author
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Kitap
Mevcut
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Inventory number Full call number Barcode Date last seen Price effective from Koha item type
    Library of Congress Classification     Non-fiction Mehmet Akif Ersoy Merkez Kütüphanesi Mehmet Akif Ersoy Merkez Kütüphanesi Genel Koleksiyon 10/11/2016 Satın Alma 234.93 255.07.02.01.06- TS183 .S53 2016 041260 10/11/2016 10/11/2016 Kitap
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