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CS318 Decision Support Systems

CS318 Decision Support Systems. Rationale : This course aims to provide students with fundamental knowledge on decision support systems for managers and IS developers.

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CS318 Decision Support Systems

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  1. CS318 Decision Support Systems • Rationale: This course aims to provide students with fundamental knowledge on decision support systems for managers and IS developers. This discipline is a combination of several different disciplines: mathematical models, database systems, expert systems, neural networks, data mining, operations research, management science, user interface, graphics techniques and programming techniques.

  2. Course Outline: PART A • I Management support systems: An Overview • 1. Managers and Computerized Support • 2. Decision Support Systems (DSS) • 3. Development process of a DSS • II Systems, Mathematic Models, and Decision Support • 1. Systems • 2. Models • 3. The Modeling Process • 4. Critical Success Factors • 5. Human Cognition and Decision Styles • 6. Making Decision in Group • III Decision Support Systems : An Overview • 1. The Illustrative case for DSS • 2. Introduction: What is a DSS; • 3. Characteristic and Capabilities of DSS • 4. Components of DSS • 5. Classification of DSS and Their Support

  3. IV Data Management • 1 Sources of Data • 2. atabase and Database Management Systems: An Introduction • 3 Fourth-generation Systems • 4 Object-oriented Databases • 5.Enterprise Decision Support and The Information Warehouse • 6.Intelligent Databases • V Modeling and Model Management • 1. Modeling in MSS • 2. Static and Dynamic Models • 3. Treating Certainty, Uncertainty, and Risk • 4. Types of Modeling: Decision Trees, Mathematical Programming, Simulation, Heuristic Programming, Influence Diagrams, Forecasting, Spreadsheet, Multi- dimensional Modeling • 5. Model Base Structure and Management • VI User Interface • 1. User Interfaces: An Overview • 2. Interface Modes (Styles): Graphics and Graphical User Interface (GUI), Multimedia and Hypermedia, Visual Interactive Modeling, Virtual Reality • 3. Geographical Information System (GIS) • 4. Natural Language Processing: An Overview and Methods • 5. Research on User Interface in MSS

  4. VII Constructing a Decision Support System • 1. Development Strategies • 2. The DSS Development Process: Life Cycle versus Prototyping • 3. Team-developed versus User-developed DSS • 4. End-User Computing and User-developed DSS • 5. Selection of a DSS Generator and Other Software Tools • 6. Developing DSS in the Windows Environment PART B • VIII Data Warehousing • 1. Basic concepts of data warehousing • 2. Data warehouse architectures • 3. Some characteristics of data warehouse data • 5. The reconciled data layer • 6. Data tranformation • 7. The derived data layer • 8. The user interface • IX Data Mining • Overview on data mining • Association rules • Classification • Clustering • Some other data mining problems

  5. X Neural Networks in Decision Support • 1. Introduction • 2. ANN representations • 3. Perceptron Training • 4. Multilayer networks and Backpropagation algorithm • 5. Remarks on the Backpropagation algorithm • 6. Neural network application development • 7. Benefits and limitations of ANN • 8. ANN Applications in decision support References [1] Turban, E., Aronson,J.E., Decision Support Systems and Intelligent Systems- 6th Edition, Prentice-Hall, 2001. Instructors: Part A: Dr. Le Van Duc Part B: Assoc. Prof. Dr. Duong Tuan Anh

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