Assessing the Reliability of Complex Networks through Hybrid Intelligent Systems

  • D.E. D. Torres
  • C.M. S. Rocco
Conference paper


This paper describes the application of Hybrid Intelligent Systems in a new domain: reliability of complex networks. The reliability is assessed by employing two algorithms (TREPAN and Adaptive Neuro-Fuzzy Inference Systems (ANFIS)), both belonging to the Hybrid Intelligent Systems paradigm. TREPAN is a technique to extract linguistic rules from a trained Neural Network, whereas ANFIS is a method that combines fuzzy inference systems and neural networks. In the experiment presented, the structure function of the complex network analyzed is properly emulated by training both models on a subset of possible system configurations, generated by a Monte Carlo simulation and an appropriate Evaluation Function. Both approaches are able to successfully describe the network status through a set of rules, which allows the reliability assessment


Fuzzy Model Fuzzy Inference System Fuzzy Neural Network ANFIS Model Hybrid Intelligent System 
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Copyright information

© Springer-Verlag/Wien 2005

Authors and Affiliations

  • D.E. D. Torres
    • 1
  • C.M. S. Rocco
    • 1
  1. 1.Facultad de IngenieríaUniversidad Central de VenezuelaVenezuela

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