Fuzzy graphs in fuzzy neural networks


  • Sameena Kalathodi National Institute of Technology.
  • M. S. Sunitha National Institute of Technology.




Fuzzy graph, Strongest path, Fuzzy neuron, OR fuzzy neuron.


In this paper we observe that, the fuzzy neural network architecture is isomorphic to the fuzzy graph model and the output of a fuzzy neural network with OR fuzzy neuron is equal to the strength of strongest path between the input layer (particular input neuron/neurons) and the out put layer(particular output neuron). We explain this result through an example, which describes the marketability of text books of kindergarten classes.

Author Biographies

Sameena Kalathodi, National Institute of Technology.

Department of Mathematics.

M. S. Sunitha, National Institute of Technology.

Department of Mathematics.


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[2] A. M Ibrahim, Introduction to Applied Electronics, Prentice Hall Of India, (1999).

[3] L. H Tsoukalas, R. E Uhrig, fuzzy and Neural Approaches in Engineering, John Wiley & Sons, (1997).

[4] S. Rajesekaren, G. A Vijayalakshmi Pai, Neural Networks, Fuzzy Logic and Genetic Algorithms, Synthesis and Applications, Prentice- Hall of India, (2003).

[5] Timothy J Ross , Fuzzy Logic with Engineering Application, Mc GrawHill, (1997).

[6] Jang. J. S. R., Sun. C. T, Mizutani. E, Neuro - Fuzzy and soft computing, Prentice - Hall upper saddle River, N J, (1997).

How to Cite

S. Kalathodi and M. S. Sunitha, “Fuzzy graphs in fuzzy neural networks”, Proyecciones (Antofagasta, On line), vol. 28, no. 3, pp. 239-252, 1.