A building of the genetic-neural network for sinter's burning through point

Abstract

This paper presents the genetic-neural network for sinter's burning through point since BTP control is the most important, which is tightly coupled with sinter ore quality. In offline, advanced genetic algorithm (GA) is used to optimize the original connection weights and thresholds, and during online, hybrid neural network (HNN) inherited from the principle of backpropagation is used to train the map parameters and improve the system precision in each sampling period. The results obtained from the actual process demonstrate that the performance and capability of the proposed system are superior.