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Artificial Neural Networks in Decision Support Systems

In: Handbook on Decision Support Systems 1

Author

Listed:
  • Dursun Delen

    (Oklahoma State University)

  • Ramesh Sharda

    (Oklahoma State University)

Abstract

This paper introduces the concepts of neural networks and presents an overview of the applications of neural networks in decision support systems (DSS). Neural networks can be viewed as supporting at least two types of DSS: data driven and model-driven. First, neural networks can be employed as data analysis tools for forecasting and prediction based on historical data in a data-driven DSS. Second, neural networks also can be viewed as a class of quantitative models to be used in a model-driven DSS. After describing the basics of neural networks, we present selected applications of neural networks in DSS. We then describe a web-based DSS built by us that employs a neural network. This DSS has been built to assist a Hollywood decision maker in making decisions on a movie’s parameters. The paper concludes with a list of issues to consider in employing a neural network for a DSS application.

Suggested Citation

  • Dursun Delen & Ramesh Sharda, 2008. "Artificial Neural Networks in Decision Support Systems," International Handbooks on Information Systems, in: Handbook on Decision Support Systems 1, chapter 26, pages 557-580, Springer.
    • Handle: RePEc:spr:ihichp:978-3-540-48713-5_26
    DOI: 10.1007/978-3-540-48713-5_26
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