[PDF] Multicriteria Decision Aid And Artificial Intelligence eBook

Author : Michael Doumpos
Publisher : John Wiley & Sons
Page : 328 pages
File Size : 46,26 MB
Release : 2013-02-01
Category : Business & Economics
ISBN : 1118522494

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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.

Author : Athanasios Spyridakos
Publisher : Springer Nature
Page : 179 pages
File Size : 26,86 MB
Release : 2023-08-16
Category : Business & Economics
ISBN : 3031348923

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This book is focused on the application of methodological approaches and systems of multiple criteria decision analysis (MCDA) in the field of resource management. Resource management constitutes a major challenge of modern times. The book comprehensively examines cases of human resources, material resources and natural resources in particular. It focuses on the efficient utilization of these resources to achieve sustainability of economic, environmental and social aspects. Also, the book presents methodological tools which aim to support the decision making at operational, executive and strategic levels.The book presents recent results of scientific research in the field of MCDA and its applications to resource management. It investigates the resource management challenges and introduces innovative methodological approaches and systems for addressing these resources management issues.

Author : Miquel Sànchez-Marrè
Publisher : Springer Nature
Page : 826 pages
File Size : 13,18 MB
Release : 2022-03-28
Category : Computers
ISBN : 3030877906

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This book, with invaluable contributions of Professor Franz Wotawa in chapters 5 and 7, presents the potential use and implementation of intelligent techniques in decision making processes involved in organizations and companies. It provides a thorough analysis of decisions, reviewing the classical decision theory, and describing usual methods for modeling the decision process. It describes the chronological evolution of Decision Support Systems (DSS) from early Management Information Systems until the appearance of Intelligent Decision Support Systems (IDSS). It explains the most commonly used intelligent techniques, both data-driven and model-driven, and illustrates the use of knowledge models in Decision Support through case studies. The author pays special attention to the whole Data Science process, which provides intelligent data-driven models in IDSS. The book describes main uncertainty models used in Artificial Intelligence to model inexactness; covers recommender systems; and reviews available development tools for inducing data-driven models, for using model-driven methods and for aiding the development of Intelligent Decision Support Systems.

Author : Nikolaos F. Matsatsinis
Publisher : Springer Science & Business Media
Page : 517 pages
File Size : 10,95 MB
Release : 2012-12-06
Category : Business & Economics
ISBN : 146151147X

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Intelligent Support Systems for Marketing Decisions examines new product development, market penetration strategies, and other marketing decisions utilizing a confluence of methods, including Decision Support Systems (DSS), Artificial Intelligence in Marketing and Multicriteria Analysis. The authors systematically examine the use and implementation of these methodologies in making strategic marketing decisions. Part I discusses the basic concepts of multicriteria analysis vis-à-vis marketing decisions and in new product development situations. Part II presents basic concepts from the fields of Information Systems, Decision Support Systems, and Intelligent Decision Support Methods. In addition, specialized categories of DSS (multicriteria DSS, web-based DSS, group DSS, spatial DSS) are discussed in terms of their key features and current use in marketing applications. Part III presents IDSS and a multicriteria methodology for new product development. Further chapters present a developmental strategy for analyzing, designing, and implementing an Intelligent Marketing Decision Support System. The implementation discussion is illustrated with a real-world example of the methods and system in use.

Author : Jatinder N.D. Gupta
Publisher : Springer Science & Business Media
Page : 508 pages
File Size : 10,50 MB
Release : 2007-03-30
Category : Technology & Engineering
ISBN : 1846282314

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This book will be bought by researchers and graduates students in Artificial Intelligence and management as well as practising managers and consultants interested in the application of IT and information systems in real business environment.

Author : Salvatore Greco
Publisher : Springer Nature
Page : 446 pages
File Size : 23,65 MB
Release : 2022-05-31
Category : Business & Economics
ISBN : 3030963187

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This book presents a collection of essays written by leading researchers to honor Roman Słowiński’s major scholarly interests and contributions. He is well-known for conducting extensive research on methodologies and techniques for intelligent decision support, where he combines operational research and artificial intelligence. The book reconstructs his main contributions, presents cutting-edge research and provides an outlook on the most promising and advanced domains of computer science and multiple criteria decision aiding. The respective chapters cover a wide range of related research areas, including decision sciences, ordinal data mining, preference learning and multiple criteria decision aiding, modeling of uncertainty and imprecision in decision problems, rough set theory, fuzzy set theory, multi-objective optimization, project scheduling and decision support applications. As such, the book will appeal to researchers and scholars in related fields.

Author : Rafael Valencia-García
Publisher : Springer
Page : 252 pages
File Size : 27,57 MB
Release : 2018-02-07
Category : Technology & Engineering
ISBN : 3319740024

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This book presents innovative and high-quality research regarding advanced decision support systems (DSSs). It describes the foundations, methods, methodologies, models, tools, and techniques for designing, developing, implementing and evaluating advanced DSSs in different fields, including finance, health, emergency management, industry and pollution control. Decision support systems employ artificial intelligence methods to heuristically address problems that are cannot be solved using formal techniques. In this context, technologies such as the Semantic Web, linked data, big data, and machine learning are being applied to provide integrated support for individuals and organizations to make more rational decisions. The book is organized into two parts. The first part covers decision support systems for industry, while the second part presents case studies related to clinical emergency management and pollution control.

Author : Ilker Ozsahin
Publisher : Bentham Science Publishers
Page : 316 pages
File Size : 16,4 MB
Release : 2021-11-18
Category : Computers
ISBN : 168108872X

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This book provides an ideal foundation for readers to understand the application of artificial intelligence (AI) and machine learning (ML) techniques to expert systems in the healthcare sector. It starts with an introduction to the topic and presents chapters which progressively explain decision-making theory that helps solve problems which have multiple criteria that can affect the outcome of a decision. Key aspects of the subject such as machine learning in healthcare, prediction techniques, mathematical models and classification of healthcare problems are included along with chapters which delve in to advanced topics on data science (deep-learning, artificial neural networks, etc.) and practical examples (influenza epidemiology and retinoblastoma treatment analysis). Key Features: - Introduces readers to the basics of AI and ML in expert systems for healthcare - Focuses on a problem solving approach to the topic - Provides information on relevant decision-making theory and data science used in the healthcare industry - Includes practical applications of AI and ML for advanced readers - Includes bibliographic references for further reading The reference is an accessible source of knowledge on multi-criteria decision-support systems in healthcare for medical consultants, healthcare policy makers, researchers in the field of medical biotechnology, oncology and pharmaceutical research and development.

Author : Surekha Borra
Publisher : Walter de Gruyter GmbH & Co KG
Page : 221 pages
File Size : 22,72 MB
Release : 2019-10-21
Category : Computers
ISBN : 3110618710

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Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), knowledge based systems (KBS), data mining, artificial intelligence (AI) and include several systems developed from the study of expert systems (ES), genetic algorithms (GA), artificial neural networks (ANN) and fuzzy-logic systems The use of automatic decision support systems in design and manufacturing industry, healthcare and commercial software development systems has the following benifits: Cost savings in companies, due to employment of expert system technology. Fast decision making, completion of projects in time and development of new products. Improvement in decision making capability and quality. Usage of Knowledge database and Preservation of expertise of individuals Eases complex decision problems. Ex: Diagnosis in Healthcare To address the issues and challenges related to development, implementation and application of automatic and intelligent prediction and decision support systems in domains such as manufacturing, healthcare and software product design, development and optimization, this book aims to collect and publish wide ranges of quality articles such as original research contributions, methodological reviews, survey papers, case studies and/or reports covering intelligent systems, expert prediction systems, evaluation models, decision support systems and Computer Aided Diagnosis (CAD).

Author : Constantin Zopounidis
Publisher : Springer Science & Business Media
Page : 191 pages
File Size : 38,79 MB
Release : 2013-03-09
Category : Business & Economics
ISBN : 1475728859

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This book provides a new point of view on the subject of business failure prediction, through the application of multicriteria analysis methods. The aim of the book is to provide a review of the research in the area and to explore the adequacy of these methods to one of the most complex problems in the area of financial management. In addition, the book explores the applications of the methods so that it can become a very useful tool for researchers and practitioners. The analysis of the modeling and the results in these applications provides the background for further employment of the methods.