Notice of RetractionLevenberg-Marquardt neural network for prediction of material mechanical properities
In this study we are trying with the Levenberg-Marquardt neural network model to make an effective prediction of material mechanical properties. By using second derivative information, the network convergence speed is promoted and the generalization performance is enhanced. Taking the wheat straw-reinforced composite for instance, the nonlinear mapping is set up from four influence factors (mold temperature, mold pressure, fibre content and time ) to its tensile strength and toughness. The simulation results show the founded network model has preferable learning and generalization capabilities, which performs effectively in predicting composite mechanical properties. Besides, the model is used to optimize process parameters of compression molding and find the range of best parameters.