-->
Course Title: Decision Support and Expert System
Course no: CSC-460 Full Marks: 70+10+20
Credit hours: 3 Pass Marks: 28+4+8
Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)
Course Synopsis: Use of Artificial Intelligence.
Goal: This course introduces fundamental concept of decision support and expert systems and its application on neural networks.
Course Content:
Unit 1. Introduction to Management Support Systems 2 Hrs.
Unit 2. Systems, Modeling, and Support for Decision Making 2 Hrs.
Unit 3. Overview of Decision Support Systems (DSS) 1 Hr.
Unit 4. DSS Data Management 2 Hrs.
Unit 5. Modeling and DSS Model Management 3 Hrs.
Unit 6. DSS User Interface 2 Hrs.
Unit 7. Constructing a DSS 1 Hr.
Unit 8. Organizational DSS (ODSS) and Advanced Topics 3 Hrs.
Unit 9. Group Decision Support Systems (GDSS) 3 Hrs.
Unit 10. Distributed Group Support Systems 3 Hrs.
Unit 11. Executive Information and Support Systems 3 Hrs.
Unit 12. Overview of Applied Artificial Intelligence (AI) and Problem Solving2 Hrs.
Unit 13. Fundamentals of Expert Systems 1 Hr.
Unit 14. Knowledge Acquisition and Validation 3 Hrs.
Unit 15. Knowledge Representation 4 Hrs.
Unit 16. Inference, Explanations, and Uncertainty 4 Hrs.
Unit 17. Building Expert Systems: Process and Tools 4 Hrs.
Unit 18. Fundamentals of Artificial Neural Networks 3 Hrs.
Unit 19. Neural Network Applications 2 Hrs.
Laboratory works: Designing a simple decision support system tool
Text Books: Decision Support and Expert Systems: Management Support Systems, Efriam Turban, 4th Edition, 1995, Prentice-Hall.
Developing Knowledge-Based Systems Using VP-Expert, Dorothy G. Dologite, 1993, Macmillan.
Homework
Assignment: Assignment should be given in throughout the semester.
Computer Usage: No specific
Prerequisite: C, C++, Data Structure
Category Content: Science Aspect: 50%
Design Aspect: 50%
No comments:
Post a Comment