Based on Genetic Algorithms and Artificial Neural Network Algorithms to Optimize the Structure Design and Implementation of Crane

Abstract

This paper by using the finite element method, orthogonal test method, BP neural network and genetic algorithm to optimization of crane structure system. A dynamic optimal computational model for the complex structure system with genetic algorithm (GA)and BP neural network(NN)was presented．Instead of the traditional finite element model，this model can be used for the fast re-analysis for the vibration system．Firstly，the harmonic response kinetics analysis can be processed on a crane structure system and can find out them ode frequency which has the strongest effect on the system dynamic behavior．Secondly，from the sensitivity analysis，the design variables which are more sensitive to the system dynamic behavior can be confirmed as the input variables． Then an orthogonal experimentation was used in choosing the training sample data and the sample data was calculated through the finite element model．The artificial neural network model which presented the dynamic behavior of the structure vibration was established．At last，the neural network model will be optimized through the generic algorithm and the optimal parameters of the structure dynamic behavior will be obtained．