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- W2386364093 abstract "The platform of mechanical properties predication for welded joints based on neural network was established in this paper. It could be achieved to predict mechanical properties of welded joints of alloy steel,titanium alloy and aluminum alloy. The predictions included tensile strength,yield strength,elongation and section shrinkage,and simultaneously it could analyze the influence of parameters on the mechanical properties of joints. The core of algorithm was the application of genetic algorithm optimizes BP neural network connection weights. This algorithm was good at global search as well as was not easy involved into a local optimization,so it could make the predictions own a good generalization function as well as high predictive accuracy. The system also provided an alternative algorithm LM. It was the combination of Gauss-Newton algorithm with gradient descent algorithm. It owned self-learning neural network characteristics,rapid convergence characteristics of Gauss-Newton algorithm and local search characteristics of gradient descent algorithm,therefore,it had good generalization function and high predictive accuracy." @default.
- W2386364093 created "2016-06-24" @default.
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- W2386364093 date "2010-01-01" @default.
- W2386364093 modified "2023-09-23" @default.
- W2386364093 title "Platform of mechanical properties predication for welded joints based on neural network optimized by genetic algorithm" @default.
- W2386364093 hasPublicationYear "2010" @default.
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