Verifying Three Nodes Optimization Based on LM-BP Neural Network and Hybrid Genetic Algorithm

Abstract:

Taking the minimum to cylinder thrust force, turntable force and boom force as the objective function then establish the optimization mathematical model of the verifying three nodes, taking BP Neural Network as the main method instead of the cumbersome formula derivation. This article puts forward a Hybrid Genetic Algorithm flow set of solving pareto optimal solution, It is achieved by mixed-using Niche Technology, Groups Sorting Technology. The optimal position of the arm verifying three nodes is conformed by programming using Matlab genetic algorithm toolbox. And the force of the fuel tank , boom and turntable is effectively mitigated. This gives a appropriate reference for the next boom verifying three nodes position to determine and the optimal design of similar structures in other engineering machinery.

• Periodical: Applied Mechanics and Materials (Volumes 385-386)
• Pages: 348-351
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.385-386.348
• Online since: August 2013
• Authors: Xin Li, Zhong Peng Zhang, Shi Lin Shen, Fei Xie
• Keywords: BP Neural Network (BPNN), Hybrid Genetic Algorithm, Optimal Design, Verifying Three Nodes

References

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