BP Neural Network Research Based on Three Convergence Improved LM Algorithm
Xiu Cai Guo, Sai Hua Shang
Abstract
Xiu Cai Guo, Sai Hua Shang
Abstract
In order to solve the practical application problem, which traditional neural network takes too long and compute complexly, on the basis of the LM algorithm, combined with mathematical optimization theory, identify the three convergence Improved LM algorithm applied to BP neural network , that improved LMBP algorithm. Simulation results show that the improved LMBP algorithm in convergence time and goodness of fit both have better results, and the algorithm is general and can be produced by obtaining national sample of various scenarios, using the algorithm to predict, to better guidance on production.
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In order to solve the practical application problem, which traditional neural network takes too long and compute complexly, on the basis of the LM algorithm, combined with mathematical optimization theory, identify the three convergence Improved LM algorithm applied to BP neural network , that improved LMBP algorithm. Simulation results show that the improved LMBP algorithm in convergence time and goodness of fit both have better results, and the algorithm is general and can be produced by obtaining national sample of various scenarios, using the algorithm to predict, to better guidance on production.
Key concepts: Convergence (economics), Artificial neural network, Algorithm, Computer science, Sample (material), Optimization algorithm, Basis (linear algebra), Mathematical optimization