A Modified Teaching and Learning Based Optimization Algorithm and Application in Deep Neural Networks Optimization for Electro-Discharge Machining

Abstract

In order to improve the output precision of depth neural networks, an improved teaching and learning optimization algorithm is proposed to optimize the weights and thresholds of depth neural networks. The algorithm is improved according to the teaching and learning phases of the basic teaching and learning algorithms. The performance of the algorithm is tested by electro-discharge machining (EDM) experiments. The results show that the algorithm has the advantages of fast convergence and high solution accuracy.