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Exploring Intelligent Decision Support Systems
(Englisch)
Current State and New Trends
Valencia-García, Rafael & Paredes-Valverde, Mario Andrés & Salas-Zárate, María del Pilar & Alor-Hernández, Giner

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Exploring Intelligent Decision Support Systems

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  • Springer Basel AG
    Picassoplatz 4
    CH-4010 Basel
    +41 61 2050707
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  • 203140674

Produktbeschreibung

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


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.


FINALGRANT: A Financial Linked Data Graph Analysis and Recommendation Tool.- Constructing and Interrogating Actor Histories.- Challenges in the Design of Decision Support Systems for Port and Maritime Supply Chains.- Analyzing the Impact of a Decision Support System on a Medium Sized Apparel Company.- A Multicriteria Decision Support System Framework for Computer Selection.- An Agent-Based Memetic Algorithm for Solving Three-Level Freight Distribution Problems.
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). The first part covers decision support systems for industry, while the second part presents case studies related to clinical emergency management and pollution control.



Inhaltsverzeichnis

FINALGRANT: A Financial Linked Data Graph Analysis and Recommendation Tool.- Constructing and Interrogating Actor Histories.- Challenges in the Design of Decision Support Systems for Port and Maritime Supply Chains.- Analyzing the Impact of a Decision Support System on a Medium Sized Apparel Company.- A Multicriteria Decision Support System Framework for Computer Selection.- An Agent-Based Memetic Algorithm for Solving Three-Level Freight Distribution Problems.


Klappentext

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.




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



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