Multicriteria decision aid and artificial intelligence: links, theory and applications
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Hoboken, N.J.
Wiley-Blackwell
2013
|
| Schlagwörter: | |
| Beschreibung: | Includes bibliographical references and index "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"-- |
| Umfang: | xvi, 351 p. |
| ISBN: | 9781118522509 |
Internformat
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| 100 | 1 | |a Doumpos, Michael |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Multicriteria decision aid and artificial intelligence |b links, theory and applications |c edited by Michael Doumpos and Evangelos Grigoroudis |
| 264 | 1 | |a Hoboken, N.J. |b Wiley-Blackwell |c 2013 | |
| 300 | |a xvi, 351 p. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
| 500 | |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. | ||
| 500 | |a 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. | ||
| 500 | |a 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"-- | ||
| 505 | 0 | |a Machine generated contents note: List of Contributors Preface Part One The Contributions of Intelligent Techniques in Multicriteria Decision Aiding 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 1.3 Computational Intelligence in MCDA 1.3.1 Statistical Learning and Data Mining 1.3.2 Fuzzy Modeling 1.3.3 Metaheuristics 1.4 Conclusions References 2 Intelligent Decision Support Systems 2.1 Introduction 2.2 Fundamentals of Human Decision Making 2.3 Decision Support System 2.4 Intelligent Decision Support Systems 2.4.1 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 | |
| 650 | 4 | |a Künstliche Intelligenz | |
| 650 | 4 | |a Multiple criteria decision making | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 0 | 7 | |a Künstliche Intelligenz |0 (DE-588)4033447-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Entscheidung bei mehrfacher Zielsetzung |0 (DE-588)4113444-8 |2 gnd |9 rswk-swf |
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| 689 | 0 | 1 | |a Künstliche Intelligenz |0 (DE-588)4033447-8 |D s |
| 689 | 0 | |8 1\p |5 DE-604 | |
| 700 | 1 | |a Grigoroudis, Evangelos |e Sonstige |4 oth | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe, Hardcover |z 978-1-119-97639-4 |
| 912 | |a ZDB-30-PAD | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-029579597 | |
Datensatz im Suchindex
| _version_ | 1818982988820512768 |
|---|---|
| any_adam_object | |
| author | Doumpos, Michael |
| author_facet | Doumpos, Michael |
| author_role | aut |
| author_sort | Doumpos, Michael |
| author_variant | m d md |
| building | Verbundindex |
| bvnumber | BV044172752 |
| collection | ZDB-30-PAD |
| contents | Machine generated contents note: List of Contributors Preface Part One The Contributions of Intelligent Techniques in Multicriteria Decision Aiding 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 1.3 Computational Intelligence in MCDA 1.3.1 Statistical Learning and Data Mining 1.3.2 Fuzzy Modeling 1.3.3 Metaheuristics 1.4 Conclusions References 2 Intelligent Decision Support Systems 2.1 Introduction 2.2 Fundamentals of Human Decision Making 2.3 Decision Support System 2.4 Intelligent Decision Support Systems 2.4.1 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 |
| ctrlnum | (ZDB-30-PAD)EBC1120963 (ZDB-89-EBL)EBL1120963 (OCoLC)834611725 (DE-599)BVBBV044172752 |
| dewey-full | 658.4/033 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.4/033 |
| dewey-search | 658.4/033 |
| dewey-sort | 3658.4 233 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| id | DE-604.BV044172752 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T17:55:58Z |
| institution | BVB |
| isbn | 9781118522509 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029579597 |
| oclc_num | 834611725 |
| open_access_boolean | |
| physical | xvi, 351 p. |
| psigel | ZDB-30-PAD |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | Wiley-Blackwell |
| record_format | marc |
| spelling | Doumpos, Michael Verfasser aut Multicriteria decision aid and artificial intelligence links, theory and applications edited by Michael Doumpos and Evangelos Grigoroudis Hoboken, N.J. Wiley-Blackwell 2013 xvi, 351 p. txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index "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"-- Machine generated contents note: List of Contributors Preface Part One The Contributions of Intelligent Techniques in Multicriteria Decision Aiding 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 1.3 Computational Intelligence in MCDA 1.3.1 Statistical Learning and Data Mining 1.3.2 Fuzzy Modeling 1.3.3 Metaheuristics 1.4 Conclusions References 2 Intelligent Decision Support Systems 2.1 Introduction 2.2 Fundamentals of Human Decision Making 2.3 Decision Support System 2.4 Intelligent Decision Support Systems 2.4.1 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 Künstliche Intelligenz Multiple criteria decision making Artificial intelligence Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Entscheidung bei mehrfacher Zielsetzung (DE-588)4113444-8 gnd rswk-swf Entscheidung bei mehrfacher Zielsetzung (DE-588)4113444-8 s Künstliche Intelligenz (DE-588)4033447-8 s 1\p DE-604 Grigoroudis, Evangelos Sonstige oth Erscheint auch als Druck-Ausgabe, Hardcover 978-1-119-97639-4 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Doumpos, Michael Multicriteria decision aid and artificial intelligence links, theory and applications Machine generated contents note: List of Contributors Preface Part One The Contributions of Intelligent Techniques in Multicriteria Decision Aiding 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 1.3 Computational Intelligence in MCDA 1.3.1 Statistical Learning and Data Mining 1.3.2 Fuzzy Modeling 1.3.3 Metaheuristics 1.4 Conclusions References 2 Intelligent Decision Support Systems 2.1 Introduction 2.2 Fundamentals of Human Decision Making 2.3 Decision Support System 2.4 Intelligent Decision Support Systems 2.4.1 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 Künstliche Intelligenz Multiple criteria decision making Artificial intelligence Künstliche Intelligenz (DE-588)4033447-8 gnd Entscheidung bei mehrfacher Zielsetzung (DE-588)4113444-8 gnd |
| subject_GND | (DE-588)4033447-8 (DE-588)4113444-8 |
| title | Multicriteria decision aid and artificial intelligence links, theory and applications |
| title_auth | Multicriteria decision aid and artificial intelligence links, theory and applications |
| title_exact_search | Multicriteria decision aid and artificial intelligence links, theory and applications |
| title_full | Multicriteria decision aid and artificial intelligence links, theory and applications edited by Michael Doumpos and Evangelos Grigoroudis |
| title_fullStr | Multicriteria decision aid and artificial intelligence links, theory and applications edited by Michael Doumpos and Evangelos Grigoroudis |
| title_full_unstemmed | Multicriteria decision aid and artificial intelligence links, theory and applications edited by Michael Doumpos and Evangelos Grigoroudis |
| title_short | Multicriteria decision aid and artificial intelligence |
| title_sort | multicriteria decision aid and artificial intelligence links theory and applications |
| title_sub | links, theory and applications |
| topic | Künstliche Intelligenz Multiple criteria decision making Artificial intelligence Künstliche Intelligenz (DE-588)4033447-8 gnd Entscheidung bei mehrfacher Zielsetzung (DE-588)4113444-8 gnd |
| topic_facet | Künstliche Intelligenz Multiple criteria decision making Artificial intelligence Entscheidung bei mehrfacher Zielsetzung |
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