Using artificial neural networks to aid decision making processes

  • José E. Cano
  • Miguel Delgado
  • Ignacio Requena
Part of the Lecture Notes in Computer Science book series (LNCS, volume 540)


Ranking fuzzy numbers is very necessary when we have to make a decision with imprecise information. The comparison depends on decision-maker's subjectivity and then capturing it into algorithms is difficult. Several methods has been developed in order to ranking fuzzy numbers, each of them being subjective, but the lack of real fitness is always present.

Artificial Neural Networks (ANN) are able to model systems with unknown performance (learning their behavior) and thus ANN may be used in Decision Making Problems to disclose decision maker's unknown behavior.

In this paper, we propose ranking fuzzy numbers using ANNs. We present several experiences: We have simulated an ANN that use the Backpropagation algorithm for learning. Also we show that it is possible to take a decision using ANNs, when we have fuzzy information.


ANNs backpropagation trapezoidal fuzzy number ranking fuzzy number 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • José E. Cano
    • 1
  • Miguel Delgado
    • 1
  • Ignacio Requena
    • 1
  1. 1.Dpto. de Ciencias de la Computación e Inteligencia Artificial de laUniversidad de Granada. Facultad de CienciasGranada

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