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自然科学与工程中的许多问题都可以转化为非线性方程组的求解问题,牛顿迭代法是重要的一维及多维的迭代技术,其迭代本身对初始点非常敏感.通过消除暂态混沌神经元的模拟退火策略,产生了一种可以永久保持混沌搜索的混沌神经元,研究了由4个该混沌神经元全连接的混沌神经网络的拓扑结构,混沌神经网络中存在超混沌现象(具有3个正的李氏指数).应用神经网络超混沌系统产生牛顿迭代法的初始点,提出了基于神经网络超混沌的牛顿迭代法求解非线性方程组的新方法.变几何桁架机构综合实例表明该方法的正确性与有效性.图3,表1,参14.
Many problems in natural sciences and engineering can be transformed into solving nonlinear equations. Newton iteration is an important one-dimensional and multi-dimensional iterative technique, and the iteration itself is very sensitive to the initial point. By eliminating the transient chaos neurons , A chaotic neuron that can keep chaos search permanently is generated. The topology of chaotic neural network which is fully connected by 4 chaotic neurons is studied. There is a hyperchaotic phenomenon in the chaotic neural network (with 3 Positive Lee index.) A new method of Newton iteration method based on neural network hyperchaos is proposed to solve nonlinear equations by using neural network hyperchaos system to generate the initial point of Newton iteration method. A comprehensive example of the variable geometry truss mechanism shows that this method The correctness and effectiveness of Figure 3, Table 1, reference 14.