Editors:
- Introduces innovative intelligent approaches, methods, models and systems to effectively support decision-making in different fields
- Presents real-world and original research work
- Describes the state-of-art in the field
Part of the book series: Studies in Computational Intelligence (SCI, volume 764)
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Table of contents (11 chapters)
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Front Matter
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Decision Support Systems for Industry
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Front Matter
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Case Studies: Clinical, Emergency Management and Pollution Control
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Front Matter
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About this book
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.
Editors and Affiliations
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Departamento de Informática y Sistemas, Facultad de Informática, Universidad de Murcia, Murcia, Spain
Rafael Valencia-García, Mario Andrés Paredes-Valverde, María del Pilar Salas-Zárate
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Division of Research and Postgraduate Studies, Instituto Tecnológico de Orizaba, Orizaba, Mexico
Giner Alor-Hernández
Bibliographic Information
Book Title: Exploring Intelligent Decision Support Systems
Book Subtitle: Current State and New Trends
Editors: Rafael Valencia-García, Mario Andrés Paredes-Valverde, María del Pilar Salas-Zárate, Giner Alor-Hernández
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-74002-7
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-74001-0Published: 19 February 2018
Softcover ISBN: 978-3-319-89266-5Published: 07 June 2019
eBook ISBN: 978-3-319-74002-7Published: 07 February 2018
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XXIV, 238
Number of Illustrations: 14 b/w illustrations, 62 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Operations Research/Decision Theory