• DocumentCode
    2769155
  • Title

    A Neural Network Model for the Decision-Making Process Based on ANP

  • Author

    Matsuda, Satoshi

  • Author_Institution
    Coll. of Ind. Technol., Chiba
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1421
  • Lastpage
    1426
  • Abstract
    Many attempts have been made to develop neural network models of the intellectual activities of human beings. However, to our knowledge few attempts have been made to develop a neural network model of the process of decisionmaking, which is a typical intellectual activity. In this paper we propose a neural network model of the decision-making process based on the analytic network process by T. L. Saaty (2001). Although we, S. Matsuda (2005) previously proposed a neural network model for the decision-making process based on the analytic hierarchy process by T. L. Saaty (1972), the analytic network process is more elaborate than the analytic hierarchy process. By viewing decision making as an optimization process based on the analytic network process to satisfy many objectives to the greatest degree possible, we present a neural network model of the decision-making process. Furthermore, the model also works effectively in more practical situations where we cannot give the precise information or all the information necessary to make the decision. Finally, we apply the proposed neural network to an example and illustrate its validity through simulations.
  • Keywords
    cognition; decision making; neural nets; psychology; analytic network process; decision-making process; intellectual activities; neural network; Decision making; Educational institutions; Electronic mail; Feedforward neural networks; Feedforward systems; Humans; Natural languages; Neural networks; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2006. IJCNN '06. International Joint Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9490-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2006.246860
  • Filename
    1716271