|
|
|
|
| LEADER |
00000cam a2200000Ma 4500 |
| 001 |
ocn834611725 |
| 003 |
OCoLC |
| 005 |
20240504213016.0 |
| 006 |
m o d |
| 007 |
cr cn||||||||| |
| 008 |
121026s2013 njua ob 001 0 eng d |
| 010 |
|
|
|a 2012040171
|
| 040 |
|
|
|a E7B
|b eng
|e pn
|c E7B
|d OCLCQ
|d OCLCO
|d OCLCF
|d NLE
|d YDXCP
|d EBLCP
|d MHW
|d IDEBK
|d CDX
|d DEBSZ
|d UKDOC
|d AU@
|d DEBBG
|d OCLCQ
|d COO
|d CDS
|d OCLCQ
|d AZK
|d COCUF
|d MOR
|d PIFAG
|d MERUC
|d OCLCQ
|d ZCU
|d U3W
|d STF
|d WRM
|d NRAMU
|d ICG
|d VT2
|d INT
|d OCLCQ
|d UWO
|d OCLCQ
|d DKC
|d OCLCQ
|d UKAHL
|d DCT
|d OCLCQ
|d UKCRE
|d VLY
|d OCLCO
|d OCLCQ
|d OCLCO
|d OCLCL
|
| 019 |
|
|
|a 827207390
|a 860567585
|a 880902228
|a 889268409
|a 961671963
|a 962586471
|a 974766214
|a 974860387
|a 1018050955
|a 1043664545
|a 1069680146
|a 1081261443
|a 1110761144
|a 1153504875
|a 1162535495
|a 1290076143
|a 1303472062
|
| 020 |
|
|
|a 9781118522509
|q (e-book)
|
| 020 |
|
|
|a 1118522508
|
| 020 |
|
|
|a 9781118522509
|
| 020 |
|
|
|a 1119976391
|
| 020 |
|
|
|a 9781119976394
|
| 020 |
|
|
|z 9781119976394
|q (hardback)
|
| 020 |
|
|
|a 1118522516
|
| 020 |
|
|
|a 9781118522516
|
| 020 |
|
|
|a 1299159532
|
| 020 |
|
|
|a 9781299159532
|
| 035 |
|
|
|a (OCoLC)834611725
|z (OCoLC)827207390
|z (OCoLC)860567585
|z (OCoLC)880902228
|z (OCoLC)889268409
|z (OCoLC)961671963
|z (OCoLC)962586471
|z (OCoLC)974766214
|z (OCoLC)974860387
|z (OCoLC)1018050955
|z (OCoLC)1043664545
|z (OCoLC)1069680146
|z (OCoLC)1081261443
|z (OCoLC)1110761144
|z (OCoLC)1153504875
|z (OCoLC)1162535495
|z (OCoLC)1290076143
|z (OCoLC)1303472062
|
| 037 |
|
|
|a 1120963
|b EBL
|
| 050 |
|
4 |
|a T57.95
|b .D578 2013eb
|
| 049 |
|
|
|a HCDD
|
| 100 |
1 |
|
|a Doumpos, Michael.
|
| 245 |
1 |
0 |
|a Multicriteria decision aid and artificial intelligence :
|b links, theory and applications /
|c edited by Michael Doumpos and Evangelos Grigoroudis.
|
| 260 |
|
|
|a Hoboken, N.J. :
|b Wiley-Blackwell,
|c 2013.
|
| 300 |
|
|
|a 1 online resource (xvi, 351 pages) :
|b illustrations
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a computer
|b c
|2 rdamedia
|
| 338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
| 504 |
|
|
|a Includes bibliographical references and index.
|
| 520 |
|
|
|a "Presents recent advances in both models and systems for intelligent decision making.Organisations often face complex decisions requiring the assessment of large amounts of data. In recent years Multicriteria Decision Aid (MCDA) and Artificial Intelligence (AI) techniques have been applied with considerable success to support decision making in a wide range of complex real-world problems. The integration of MCDA and AI provides new capabilities relating to the structuring of complex decision problems in static and distributed environments. These include the handling of massive data sets, the modelling of ill-structured information, the construction of advanced decision models, and the development of efficient computational optimization algorithms for problem solving. This book covers a rich set of topics, including intelligent decision support technologies, data mining models for decision making, evidential reasoning, evolutionary multiobjective optimization, fuzzy modelling, as well as applications in management and engineering. Multicriteria Decision Aid and Artificial Intelligence: Covers all of the recent advances in intelligent decision making. Includes a presentation of hybrid models and algorithms for preference modelling and optimisation problems. Provides illustrations of new intelligent technologies and architectures for decision making in static and distributed environments. Explores the general topics on preference modelling and learning, along with the coverage of the main techniques and methodologies and applications. Is written by experts in the field. This book provides an excellent reference tool for the increasing number of researchers and practitioners interested in the integration of MCDA and AI for the development of effective hybrid decision support methodologies and systems. Academics and post-graduate students in the fields of operational research, artificial intelligence and management science or decision analysis will also find this book beneficial"--
|c Provided by publisher.
|
| 505 |
0 |
|
|a Part I The Contributions of Intelligent Techniques in Multicriteria Decision Aiding; Chapter 1 Computational intelligence techniques for multicriteria decision aiding: An overview; 1.1 Introduction; 1.2 The MCDA paradigm; 1.2.1 Modeling process; 1.2.2 Methodological approaches; 1.2.2.1 Multiobjective mathematical programming; 1.2.2.2 Multiattribute utility/value theory; 1.2.2.3 Outranking techniques; 1.2.2.4 Preference disaggregation analysis; 1.3 Computational intelligence in MCDA.
|
| 505 |
8 |
|
|a 1.3.1 Statistical learning and data mining1.3.1.1 Artificial neural networks; 1.3.1.2 Rule-based models; 1.3.1.3 Kernel methods; 1.3.2 Fuzzy modeling; 1.3.2.1 Fuzzy multiobjective optimization; 1.3.2.2 Fuzzy preference modeling; 1.3.3 Metaheuristics; 1.3.3.1 Evolutionary methods and metaheuristics in multiobjective optimization; 1.3.3.2 Preference disaggregation with evolutionary techniques; 1.4 Conclusions; References; Chapter 2 Intelligent decision support systems; 2.1 Introduction; 2.2 Fundamentals of human decision making; 2.3 Decision support systems.
|
| 505 |
8 |
|
|a 2.4 Intelligent decision support systems2.4.1 Artificial neural networks for intelligent decision support; 2.4.2 Fuzzy logic for intelligent decision support; 2.4.3 Expert systems for intelligent decision support; 2.4.4 Evolutionary computing for intelligent decision support; 2.4.5 Intelligent agents for intelligent decision support; 2.5 Evaluating intelligent decision support systems; 2.5.1 Determining evaluation criteria; 2.5.2 Multi-criteria model for IDSS assessment; 2.6 Summary and future trends; Acknowledgment; References.
|
| 505 |
8 |
|
|a Part II Intelligent Technologies for Decision Support and Preference ModelingChapter 3 Designing distributed multi-criteria decision support systems for complex and uncertain situations; 3.1 Introduction; 3.2 Example applications; 3.3 Key challenges; 3.4 Making trade-offs: Multi-criteria decision analysis; 3.4.1 Multi-attribute decision support; 3.4.2 Making trade-offs under uncertainty; 3.5 Exploring the future: Scenario-based reasoning; 3.6 Making robust decisions: Combining MCDA and SBR; 3.6.1 Decisions under uncertainty: The concept of robustness; 3.6.2 Combining scenarios and MCDA.
|
| 505 |
8 |
|
|a 3.6.3 Collecting, sharing and processing information: A distributed approach3.6.4 Keeping track of future developments: Constructing comparable scenarios; 3.6.5 Respecting constraints and requirements: Scenario management; 3.6.6 Assisting evaluation: Assessing large numbers of scenarios; 3.6.6.1 Comparing single scenarios: Exploring the stability of consequences; 3.6.6.2 Considering multiple scenarios: Aggregation techniques; 3.7 Discussion; 3.8 Conclusion; Acknowledgment; References; Chapter 4 Preference representation with ontologies; 4.1 Introduction; 4.2 Ontology-based preference models.
|
| 546 |
|
|
|a English.
|
| 650 |
|
0 |
|a Multiple criteria decision making.
|
| 650 |
|
0 |
|a Artificial intelligence.
|
| 650 |
|
7 |
|a artificial intelligence.
|2 aat
|
| 650 |
|
7 |
|a Artificial intelligence
|2 fast
|
| 650 |
|
7 |
|a Multiple criteria decision making
|2 fast
|
| 700 |
1 |
|
|a Grigoroudis, Evangelos.
|
| 758 |
|
|
|i has work:
|a Multicriteria decision aid and artificial intelligence (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGbgyX4W3D9hyKxwTRHX3P
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a Doumpos, Michael.
|t Multicriteria Decision Aid and Artificial Intelligence : Links, Theory and Applications.
|d New York : Wiley, ©2013
|z 9781119976394
|
| 856 |
4 |
0 |
|u https://ebookcentral.proquest.com/lib/holycrosscollege-ebooks/detail.action?docID=1120963
|y Click for online access
|
| 903 |
|
|
|a EBC-AC
|
| 994 |
|
|
|a 92
|b HCD
|