Exploring Intelligent Decision Support Systems [electronic resource] : Current State and New Trends /
Contributor(s): Valencia-García, Rafael [editor.] | Paredes-Valverde, Mario Andrés [editor.] | Salas-Zárate, María del Pilar [editor.] | Alor-Hernández, Giner [editor.] | SpringerLink (Online service).
Series: Studies in Computational Intelligence: 764Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XXIV, 238 p. 76 illus., 62 illus. in color. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319740027.Subject(s): Computer Engineering
| Computational Intelligence | Artificial Intelligence | Operations Research/Decision TheoryDDC classification: 006.3 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.)
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Springer Nature eBookSummary: 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.
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.
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