Download ISE6810: Special Topics in Intelligent Decision Support Systems

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Wizard of Oz experiment wikipedia , lookup

Ecological interface design wikipedia , lookup

Gene expression programming wikipedia , lookup

Clinical decision support system wikipedia , lookup

Ethics of artificial intelligence wikipedia , lookup

Knowledge representation and reasoning wikipedia , lookup

AI winter wikipedia , lookup

History of artificial intelligence wikipedia , lookup

Incomplete Nature wikipedia , lookup

Transcript
Special Topics in Intelligent Decision Support Systems (ISE6810)
Responsible staff and department:
Dr. W.H. Ip (Industrial and Systems Engineering)
Pre-requisite:
Nil
Recommended background knowledge:
Basic understanding of computing language and database is expected.
Objectives:
This subject aims to provide student with the advance modelling and methodology for
integration of expert systems and artificial intelligence (AI) into decision support systems
(DSS). Such as integration enables AI attached to DSS components, generating and sharing
the decision making processes and to provide managerial, organization and business support
systems. A spectrum of topics will be covered with emphasis on the industrial case studies
and practical applications.
Content:
 Intelligent DSS Design
 Multiple Goals and Sensitivity Analysis
 Decision Models
 Expert System
 Neural Computing
 Genetic Algorithm
 Case-Based Reasoning
 Heuristics Algorithm
 Inference Technology
 Intelligent DSS Prototyping
Exclusion:
Nil
Learning approach:
The student will engage in a guided study in the subject. No formal lecture will be given. The
student is required by the supervisor to read specified monographs and journal publications.
The student will perform several assignments to implement different Intelligent Decision
Support Systems in different business environments. The student and supervisor will meet
frequently to discuss the progress made by the student in the subject. The final assessment of
the subject is based on the results of the assignments and a mini-project.
Assessment:
Coursework
(assignment/case studies/lab. exercises)
40%
Examination
60%
Total
100%
References:
1.
2.
3.
4.
5.
6.
E.Turban and J.Aronson,”Decision Support Systems and Intelligent Systems”,Prentice Hall (2000).
D.Berry and A.Hart,”Expert Systems:Human Issues”,New York:Chapman and Hall (1990)
J.P. Bigus,”Data Mining with Neural Networks”,New York:McGraw-Hill (1996)
K.F. Man,K.S.Tang and S.Kwong,”Genetic Algorithm”,Springer (1999).
International Journal of Decision Support Systems, North-Holland.
Journal of Management Decision,MCB University Press.
Last updated on 19 June 03.