Hybrid distributed adaptive neural router

Authors

Chiu Che Tseng, The University of Texas at Arlington
Max Garzon, University of Memphis

Abstract

This paper describes DIANNER, a Hybrid Distributed Adaptive Neural Router for a communication network based on neural networks. By combining a simple neural network for the routing decision and a rule based system for the updating and learning process, DIANNER can implement more features for the router to quickly respond to more complex and dynamically changing real world environments. Furthermore, adaptive components of the DIANNER make decisions based on local information so that global routing information is eliminated.

Publication Title

Intelligent Engineering Systems Through Artificial Neural Networks

Recommended Citation

Tseng, C., & Garzon, M. (1998). Hybrid distributed adaptive neural router. Intelligent Engineering Systems Through Artificial Neural Networks, 1998, 159-164. Retrieved from https://digitalcommons.memphis.edu/facpubs/2873