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用遗传BP网络求高聚物的ZWT非线性粘弹方程的力学参数
Solution to the Mechanical Parameters of ZWT Nonlinear Viscoelastic Equation of High Polymer by a Genetic-BP-based Neural Net
【摘要】 结合遗传算法及BP神经网络的特点 ,构建了一个新的有机体—遗传BP网络 ,并对遗传BP网络进行了测试 ,结果表明遗传BP网络在收敛速度及收敛稳定性方面都有很好的效果 ,最后给出了一个用遗传BP网络求高聚物的ZWT方程的力学参数的实例 .
【Abstract】 The new organism called Genetic BP based neural net is established, which integrates Genetic algorithm with BP neural net. To compare the performance of the Genetic BP based neural net with the traditional BP neural net, a test is carried out. It is shown that the performance of the Genetic BP based neural net in speed of convergence and stability of convergence is very good. An application of Genetic BP based neural net to solve the mechanical parameters of ZWT nonlinear viscoelastic equation of high polymer is conducted.
【关键词】 BP网络;
遗传算法;
热区;
高聚物;
力学参数;
【Key words】 BP neural net; Genetic algorithm; hot zone; high polymer; mechanical parameter;
【Key words】 BP neural net; Genetic algorithm; hot zone; high polymer; mechanical parameter;
- 【文献出处】 宁波大学学报(理工版) ,Journal of Ningbo University(Natural Science & Engineering Edition) , 编辑部邮箱 ,2002年01期
- 【分类号】TP183
- 【下载频次】94