Recent Advances in Decision Making

183 Pages·2009·3.3 MB·English

by  Lakhmi C. Jain

ElisabethRakus-Andersson,RonaldR.Yager,NikhilIchalkaranje,
andLakhmiC.Jain(Eds.)
RecentAdvancesinDecisionMaking
StudiesinComputationalIntelligence,Volume222
Editor-in-Chief
Prof.JanuszKacprzyk
SystemsResearchInstitute
PolishAcademyofSciences
ul.Newelska6
01-447Warsaw
Poland
E-mail:[email protected]
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ISBN978-3-642-01529-8 ISBN978-3-642-02186-2
Elisabeth Rakus-Andersson,RonaldR.Yager,
Nikhil Ichalkaranje,and Lakhmi C.Jain (Eds.)
Recent Advances in Decision
Making
123
Prof.ElisabethRakus-Andersson Dr.NikhilIchalkaranje
BlekingeInstituteofTechnology SchoolofElectricaland
SchoolofEngineering InformationEngineering
DepartmentofMathematicsandScience UniversityofSouthAustralia
S-37179Karlskrona SouthAustraliaSA5095
Sweden Australia
E-mail:[email protected]
Prof.LakhmiC.Jain
RonaldR.Yager SchoolofElectricalandInformation
IonaCollege Engineering
MachineIntelligenceInstitute UniversityofSouthAustralia
715N.Avenue Adelaide
NewRochelleNY10801-1890 MawsonLakesCampus
USA SouthAustraliaSA5095
E-mail:[email protected] Australia
E-mail:[email protected]
ISBN 978-3-642-02186-2 e-ISBN 978-3-642-02187-9
DOI 10.1007/978-3-642-02187-9
Studiesin Computational Intelligence ISSN1860949X
Library of Congress Control Number:Applied for
(cid:2)c 2009 Springer-VerlagBerlin Heidelberg
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Preface
It is not only the vast amount of data but knowledge extraction and processing play an
important role in the design of the decision support systems. Sensible decision support
systems are required in virtually every field including business, healthcare, defence
and so on [1]. The design of decision support systems is also dependent on factors
such as changing sets of circumstances, uncertainty, incomplete set of data. Intelligent
paradigms such as knowledge-based systems, artificial neural networks, fuzzy
systems, evolutionary computing paradigms, intelligent agents have contributed
immensely in the decision making process. Knowledge-based systems [2] can mimic
the performance of a human expert in a limited sense by transferring his/her
knowledge to the computer in a specific domain. Artificial neural networks are
modeled after the human brain for fusing human like intelligence in machines. Fuzzy
systems are designed to incorporate human like reasoning capability in machines.
Evolutionary systems use principles inspired by natural population genetics and are
applied in many problems including optimization. Intelligent agents can aid and
automate complex problem solving in many areas and help in effective decisions [3].
The combination of intelligent systems and decision support systems provides new
powerful tools for decision makers [4][5].
The book is a collection of selected contributions from some of the world class
researchers in the field of intelligent tools and decision making. This sample is to
demonstrate that the intelligent tools can enhance the decision making process.
We sincerely thank the contributors and reviewers for their excellent contribution.
We acknowledge the excellent support of Springer-Verlag and SCI Data Processing
Team.
Elisabeth Rakus-Andersson, Sweden
Ronald R. Yager, USA
Nikhil Ichalkaraje, Australia
Lakhmi C. Jain, Australia
VI Preface
References
[1] Tonfoni, G., Jain, L.C.: Innovations in Decision Support Systems, Advanced Knowledge
International (2003)
[2] Jain, L.C., Jain, R.K.: Hybrid Intelligent Engineering systems. World Scientific, Singapore
(1997)
[3] Phillips-Wren, G.E., Jain, L.C.: Intelligent Decision Support Systems in Agent Mediated-
Environments. IOS Press, Amsterdam (2005)
[4] Phillips-Wren, G.E., Ichalkaranje, N., Jain, L.C.: Intelligent Decision Making: An AI-
Based Approach. Springer, Heidelberg (2008)
[5] Teodorescu, H.-N., Kandel, A., Jain, L.C.: Fuzzy and Neuro-fuzzy Systems in Medicine.
CRC Press, USA (1999)
Editors
Professor Dr Elisabeth Rakus-Andersson is employed at Blekinge Institute of Tech-
nology in Karlskrona, Sweden. In her research she focuses on imprecise mathematical
theories like fuzzy set theory or rough set theory. As she has a background in mathe-
matics, she develops own models mathematically formalized and she even adapts
patterns already existing to generate new applications in medicine and technical
environments.
Ronald R. Yager is Director of the Machine Intelligence Institute and Professor of In-
formation Systems at Iona College. He is editor and chief of the International Journal of
Intelligent Systems. He has worked in the area of machine intelligence and decision
VIII Editors
making under uncertainty for over twenty-five years. He has published over 500 papers
and fifteen books. He is among the world’s top 1% most highly cited researchers with
over 7000 citations. He was the recipient of the IEEE Computational Intelligence Soci-
ety Pioneer award in Fuzzy Systems. Dr. Yager is a fellow of the IEEE, the New York
Academy of Sciences and the Fuzzy Systems Association. He was given a lifetime
achievement award by the Polish Academy of Sciences. He served at the National Sci-
ence Foundation as program director in the Information Sciences program. He was a
NASA/Stanford visiting fellow and a research associate at the University of California,
Berkeley. He has been a lecturer at NATO Advanced Study Institutes. He has been a
distinguished honorary professor at the Aalborg University Esbjerg Denmark. He is an
affiliated distinguished researcher at the European Centre for Soft Computing. He
serves on the editorial board of numerous technology journals.
Nikhil Shripal Ichalkaranje is Senior Technology Advisor in the Australian Depart-
ment of Broadband, Communications and the Digital Economy. He is also an adjunct
Senior Research Fellow at the University of South Australia. His research interests
include artificial intelligence, computer communications/networking and robotics.
Nikhil holds a Masters Degree in Computer Network Systems from Swinburne Uni-
versity of Technology Melbourne and a PhD in Computer Systems Engineering from
the University of South Australia Adelaide. Nikhil has co-edited 5 books along with
several publications in the area of artificial intelligence and their applications.
Editors IX
Professor L.C. Jain is a Director/Founder of the Knowledge-Based Intelligent
Engineering Systems (KES) Centre, located in the University of South Australia.
His interests focus on the applications of novel techniques such as knowledge-
based systems, virtual intelligent systems, defence systems, intelligence-based medi-
cal systems, e-Education and intelligent agents.
Table of Contents
1 Advances in Decision Making.................................. 1
Lakhmi C. Jain and Chee Peng Lim
2 Amount of Information and Its Reliability in the Ranking of
Atanassov’s Intuitionistic Fuzzy Alternatives .................... 7
Eulalia Szmidt and Janusz Kacprzyk
3 Fuzzy Rule Base Model Identification by Bacterial Memetic
Algorithms.................................................. 21
J´anos Botzheim, L´aszlo´ Ga´l, and La´szlo´ T. Ko´czy
4 Discovering Associations with Uncertainty from Large Databases... 45
Guoqing Chen, Peng Yan, and Qiang Wei
5 Dempster-Shafer Structures,Monotonic Set MeasuresandDecision
Making ..................................................... 67
Ronald R. Yager
6 The Development of Interpretable Decision-Making Models: A
Study in Information Granularity and Semantically Grounded
Logic Operators ............................................. 89
Witold Pedrycz
7 A General Methodology for Managerial Decision Making Using
Intelligent Techniques ........................................ 103
Vil´em Nov´ak, Irina Perfilieva, and Nadezhda G. Jarushkina
8 Supporting Decision Making via Verbalization of Data Analysis
Results Using Linguistic Data Summaries ....................... 121
Janusz Kacprzyk and Sl(cid:2)awomir Zadroz˙ny
9 Computational Intelligence in Medical Decisions Making .......... 145
Elizabeth Rakus-Andersson and Lakhmi C. Jain
Appendix...................................................... 161
Author Index.................................................. 179