Monopole-Gear Design Based on Neural Network and Modified Particle Swarm Optimization

Abstract:

In order to raise the design efficiency and get the most excellent design effect, this paper combined Particle Swarm Optimization (PSO) algorithm and put forward a new kind of neural network, which based on PSO algorithm, and the implementing framework of PSO and NARMA model. It gives the basic theory, steps and algorithm; The test results show that rapid global convergence and reached the lesser mean square error MSE) when compared with Genetic Algorithm, Simulated Annealing Algorithm, the BP algorithm with momentum term.

• Periodical: Applied Mechanics and Materials (Volumes 477-478)
• Pages: 368-373
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.477-478.368
• Online since: December 2013
• Authors: Hai Rong Fang
• Keywords: Modified Particle Swarm Optimization, Monopole-Gear, Neural Network (NN)

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