Traffm chaos and its prediction based on a nonlinear car-following model

This paper discusses the dynamic behavior and its predictions for a simulated traffic flow based on the nonlinear response of a vehicle to the leading car＇s movement in a single lane. Traffic chaos is a promising field, and chaos theory has been applied to identify and predict its chaotic movement. A simulated traffic flow is generated using a car-following model（ GM model）, and the distance between two cars is investigated for its dynamic properties. A positive Lyapunov exponent confirms the existence of chaotic behavior in the GM model. A new algorithm using a RBF NN （radial basis function neural network） is proposed to predict this traffic chaos. The experiment shows that the chaotic degree and predictable degree are determined by the first Lyapunov exponent. The algorithm proposed in this paper can be generalized to recognize and predict the chaos of short-time traffic flow series     

A survey on delayed feedback control of chaos

This paper introduces the basic idea and provides the mathematical formulation of the delayed feedback control （DFC） methodology, which has been widely used in chaos control. Stability analysis including the well-known odd number linfitation of the DFC is reviewed. Some new developments in characterizing the limitation of the DFC are presented. Various modified DFC methods, which are developed in order to overcome the odd number limitation, are also described. Finally, some open problems in this research field are discussed.     

并联Buck变换器中的混沌研究

开关式DC/DC变换器是一个强的非线性控制系统,变换器满足一定条件时,就会产生各种类型的分叉和混沌.该文采用基于主从控制的并联Buck变换器为研究对象,详细推导了并联Buck变换器的动力学方程,通过仿真得到了在一定范围内改变参数时引起的分叉和混沌现象.并且借鉴非线性动力学中的Jacobian矩阵法对系统不动点的稳定性进行了分析,通过其特征值轨迹形象说明了分叉出现的原因.     

基于Logistic映射的DCSK混沌通信系统的仿真实现

扩频序列的选择涉及扩频通信的性能,对移动通信和个人便携通信的发展均将产生重要影响.文章利用Matlab对零均值L0gistic映射的混沌序列进行仿真,分析了该序列不同于其他扩频码的特点及优势,验证了将其作为扩频序列的可行性.在此基础上,对基于该序列的混沌通信系统--DCSK进行可视化仿真,讨论了其良好的扩频码特性和抗干扰特性,认为该系统为进一步研究混沌扩频通信搭建了一个良好的仿真平台.     

Traffic chaos and its prediction based on a nonlinear car-following model

This paper discusses the dynamic behavior and its predictions for a simulated traffic flow based on the nonlinear response of a vehicle to the leading car's movement in a single lane.Traffic chaos is a promising field,and chaos theory has been applied to identify and predict its chaotic movement.A simulated traffic flow is generated using a car-following model(GM model),and the distance between two cars is investigated for its dynamic properties.A positive Lyapunov exponent confirms the existence of chaotic behavior in the GM model.A new algorithm using a RBF NN (radial basis function neural network) is proposed to predict this traffic chaos.The experiment shows that the chaotic degree and predictable degree are determined by the first Lyapunov exponent.The algorithm proposed in this paper can be generalized to recognize and predict the chaos of short-time traffic flow series.     

混沌序列在3G安全通信中的应用研究

混沌映像生成的混沌序列具有不规则和对初值敏感等优点，特别适合应用于保密通信。本文在3G安全结构的基础上．提出了一种改进的安全通信方法．它利用混沌序列来定时改变3G通信中的初始密钥，以提高资料的安全性。通过计算机模拟分析得出，在合理选择改变密钥的频率时，该方法具有在不明显增加计算时间的基础上“一次一密”的优点。     

使用遗传算法进行微波非线性电路包络仿真

介绍用于分析任意调制信号激励的微波非线性电路包络仿真技术,相应给出了线性器件的伴随模型,并将该方法发展为分析多载波调制信号激励的强非线性电路。此外,本文给出了一种求解非线性谐波平衡方程组或交调波平衡方程组的非数值方法———基于十进制编码的混沌遗传算法(DCGA),融合设计了相应的交叉和变异操作,并将混沌过程引入其中以避免陷入早熟状态,可有效地产生更优解,并加速种群的收敛。最后,给出了运用这种方法的两个计算实例。     

基于自适应模糊网络系统的径流序列预测

应用自适应模糊网络系统进行径流序列数据预测 ,并给出此类混沌数据列预测的ANFIS系统结构形式 .自适应模糊网络系统模型充分利用观测数据中的先验信息 ,预测结果精确、可靠 .最后通过实例应用证明该方法的可行性和有效性 .     

混沌-改变人类认识的新发现

介绍了混沌的概念及其主要特征 ,阐述了混沌研究的意义。混沌的发现改变了人类的认识。混沌研究对现代科学的发展产生着影响 ,自本世纪 70年代后期 ,掀起了混沌研究的世界性热潮     

基于混合递阶遗传算法的径向基神经网络学习算法及其应用

在研究径向基神经网络学习算法的基础上, 提出了一种新型的径向基神经网络学习算法———混合递阶遗传算法. 该算法将递阶遗传算法和最小二乘法的优点结合在一起, 能够同时确定径向基神经网络的结构和参数, 并具有较高的学习效率. 采用基于混合递阶遗传算法的径向基神经网络对混沌时间序列学习和预测, 取得了较好的效果.