Neurofuzzy classification and rule generation of modes of radiowave propagation

Abstract

This paper describes, in a neurofuzzy framework, a method for the classification of different modes of radiowave propagation, followed by generation of linguistic rules justifying a decision. Weight decay during neural learning helps in imposing a structure on the network, resulting in the extraction of logical rules. Use of linguistic terms at the input enables better human interpretation of the inferred rules. The effectiveness of the system is demonstrated on radiosonde data of four different seasons in India.