Recent Advances in Decision Making

2009
ISBN: 978-3-642-26932-5
Verlag: Springer

Buch, Englisch, Band 222, 179 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 300 g

Reihe: Studies in Computational Intelligence

Intelligent paradigms are increasingly finding their ways in the design and development of decision support systems. This book presents a sample of recent research results from key researchers. The contributions include: Introduction to intelligent systems in decision making - A new method of ranking intuitionistic fuzzy alternatives - Fuzzy rule base model identification by bacterial memetic algorithms - Discovering associations with uncertainty from large databases - Dempster-Shafer structures, monotonic set measures and decision making - Interpretable decision-making models - A general methodology for managerial decision making - Supporting decision making via verbalization of data analysis results using linguistic data summaries - Computational intelligence in medical decisions making.

This book is directed to the researchers, graduate students, professors, decision makers and to those who are interested to investigate intelligent paradigms in decision making.

Zielgruppe

Research

Autoren/Hrsg.

Rakus-Andersson, Elisabeth

Ichalkaranje, Nikhil

Yager, Ronald R.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Mathematik | Informatik Mathematik Operations Research
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Entscheidungstheorie, Sozialwahltheorie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Inhaltsverzeichnis

Advances in Decision Making.- Amount of Information and Its Reliability in the Ranking of Atanassov’s Intuitionistic Fuzzy Alternatives.- Fuzzy Rule Base Model Identification by Bacterial Memetic Algorithms.- Discovering Associations with Uncertainty from Large Databases.- Dempster-Shafer Structures, Monotonic Set Measures and Decision Making.- The Development of Interpretable Decision-Making Models: A Study in Information Granularity and Semantically Grounded Logic Operators.- A General Methodology for Managerial Decision Making Using Intelligent Techniques.- Supporting Decision Making via Verbalization of Data Analysis Results Using Linguistic Data Summaries.- Computational Intelligence in Medical Decisions Making.