Training set generation using fuzzy logic and dynamic chromosome based Genetic Algorithms for plant identifiers

Abstract

Training set is one of the main critical sections in Neural Network, generating of it with prior knowledge can be extremely efficient. In this paper we have tried to explore the potential of using previously generated training set (not randomly) for the training of Dynamic Neural Network. The neural network was used as the core of identifier which tries to identify the internal behavior of structure-unknown non-linear time variant dynamic system.