Optimizing Tensile Strength and Yield Point of Steel Bar with Artificial Neural Network with Enhanced Parallel Cat Swarm Optimizer

摘要

In this paper, the process of optimization of chemical concentration of steel bar has been proposed which affects the tensile strength and yield point of steel bar. An Enhanced Parallel Cat Swarm Optimization (EPCSO) was used along with three layer feed forward ANN to optimize the result. The Enhanced Parallel Cat Optimization (EPCSO) is the combination of a Parallel Cat Swarm Optimization (PCSO) and a Taguchi Method which gives better performance and accuracy as compare to the other Particle Swarm Optimization (PSO)-based algorithms for solving the optimization problems. For optimizing the tensile strength and yield point of steel bar EPCSO-based ANN can give better accurate results than the TPSO-based ANN.