APPLICATION OF NEURAL NETWORKS AND MACHINE LEARNING IN NETWORK DESIGN

Communication network design is becoming increasingly complex, involvi ng making networks more usable, affordable, and reliable. To help with this, we have proposed an expert network designer (END) for configuri ng, modeling, simulating, and evaluating large structured computer net works, employing artificial intelligence, knowledge representation, an d network simulation tools, In this paper, we present a neural network /knowledge acquisition machine-learning approach to improve END's effi ciency in solving the network design problem and to extend its scope t o acquire new networking technologies, learn new network design techni ques, and update the specifications of existing technologies.