A Hybrid Model Used to Predict Flow Stress and its ApplicationReport as inadecuate

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To improved the prediction accuracy of the flow stress, a hybrid model based on the Hybrid Least Squares Support Vector Machine HLS-SVM and Mathematical Models MM was proposed. In HLS-SVM model, the optimal parameters of LS-SVM were obtained by self-adaptive Particle Swarm Optimization PSObased on Simulated Annealing SA. Simulation experiment results revealed that this model could correctly recur to the flow stress in the sample data and accurately predict the non-sample data. The efficiency and accuracy of the predicted flow stress achiieved by the proposed model were better than the methods used in most literature.


least square support vector machine ;particle swarm optimization; simulated annealing;flow stress

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Author: Yanping Wang, Bing Wu

Source: http://www.scirp.org/


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