CS1022 KNOWLEDGE BASED DECISION SUPPORT SYSTEM ANNA UNIVERSITY CHENNAI B.E DEGREE PROGRAMME COMPUTER SCIENCE AND ENGINEERING SYLLABUS

ANNA UNIVERSITY CHENNAI: CHENNAI – 600 025
B.E DEGREE PROGRAMME COMPUTER SCIENCE AND ENGINEERING
(Offered in Colleges affiliated to Anna University)
CURRICULUM AND SYLLABUS – REGULATIONS – 2004
B.E. COMPUTER SCIENCE AND ENGINEERING
LIST OF ELECTIVES FOR COMPUTER SCIENCE AND ENGINEERING

CS1022 KNOWLEDGE BASED DECISION SUPPORT SYSTEM 3 0 0 100

AIM
There has been a radical shift in the management parlance. Organizations can use Intranets and Internets to analyze various aspects about the performance and predict the future. This course aims at exposing the student to one of the important applications of the computer.
OBJECTIVE
The course has been so designed as to include.
• Development of support system
• Methods of managing knowledge
• Intelligent decision system development

UNIT I INTRODUCTION 9
Decision making, Systems, Modeling, and support – Introduction and Definition – Systems – Models – Modeling process – Decision making: The intelligence phase – The design phase - The choice phase – Evaluation: The implementation phase –Alternative Decision – Making models – Decision support systems – Decision makers - Case applications.
UNIT II DECISION SUPPORT SYSTEM DEVELOPMENT 9
Decision Support System Development: Introduction - Life cycle – Methodologies – prototype – Technology Levels and Tools – Development platforms – Tool selection – Developing DSS
Enterprise systems: Concepts and Definition – Evolution of information systems – Information needs – Characteristics and capabilities – Comparing and Integrating EIS and DSS – EIS data access, Data Warehouse, OLAP, Multidimensional analysis, Presentation and the web – Including soft information enterprise on systems - Organizational DSS – supply and value chains and decision support – supply chain problems and solutions – computerized systems MRP, ERP, SCM – frontline decision support systems.
UNIT III KNOWLEDGE MANAGEMENT 9
Introduction – Organizational learning and memory – Knowledge management –Development –methods, Technologies, and Tools – success –Knowledge management and Artificial intelligence – Electronic document management.
Knowledge acquisition and validation: Knowledge engineering – Scope – Acquisition methods - Interviews – Tracking methods – Observation and other methods – Grid analysis – Machine Learning: Rule induction, case-based reasoning – Neural computing – Intelligent agents – Selection of an appropriate knowledge acquisition methods – Multiple experts – Validation and verification of the knowledge base – Analysis, coding, documenting, and diagramming – Numeric and documented knowledge acquisition – Knowledge acquisition and the Internet/Intranets.
Knowledge representation: Introduction – Representation in logic and other schemas – Semantic networks – Production rules – Frames – Multiple knowledge representation – Experimental knowledge representations - Representing uncertainty.
UNIT IV INTELLIGENT SYSTEM DEVELOPMENT 9
Inference Techniques: Reasoning in artificial intelligence – Inference with rules: The Inference tree – Inference with frames – Model-based and case-based reasoning - Explanation and Meta knowledge – Inference with uncertainty – Representing uncertainty – Probabilities and related approaches – Theory of certainty – Approximate reasoning using fuzzy logic.
Intelligent Systems Development: Prototyping: Project Initialization – System analysis and design – Software classification: Building expert systems with tools – Shells and environments – Software selection – Hardware –Rapid prototyping and a demonstration prototype - System development –Implementation – Post implementation.

UNIT V MANAGEMENT SUPPORT SYSTEMS 9
Implementing and integrating management support systems – Implementation: The major issues - Strategies – System integration – Generic models MSS, DSS, ES – Integrating EIS, DSS and ES, and global integration – Intelligent DSS – Intelligent modeling and model management – Examples of integrated systems – Problems and issues in integration.
Impacts of Management Support Systems – Introduction – overview – Organizational structure and related areas – MSS support to business process reengineering – Personnel management issues – Impact on individuals – Productivity, quality, and competitiveness – decision making and the manager manager’s job – Issues of legality, privacy, and ethics – Intelligent systems and employment levels – Internet communication – other societal impacts – managerial implications and social responsibilities –

TOTAL : 45
TEXT BOOK
1. Efrain Turban, Jay E.Aronson, “Decision Support Systems and Intelligent Systems” 6th Edition, Pearson Education, 2001.

REFERENCES
1. Ganesh Natarajan, Sandhya Shekhar, “Knowledge management – Enabling Business Growth”, Tata McGraw-Hill, 2002.
2. George M.Marakas, “Decision Support System”, Prentice Hall, India, 2003.
3. Efrem A.Mallach, “Decision Support and Data Warehouse Systems”, Tata McGraw-Hill, 2002.