Finding global minima with a new dynamical evolutionary algorithm

A new dynamical evolutionary algorithm (DEA) based on the theory of statistical mechanics is presented. This algorithm is very different from the traditional evolutionary algorithm and the two novel features are the unique of selecting strategy and the determination of individuals that are selected to crossover and mutate. We use DEA to solve a lot of global optimization problems that are nonlinear, multimodal and multidimensional and obtain satisfactory results. Foundation item: Supported by the National Natural Science Foundation of China (No. 60133010, NO. 60073043 and No. 700/1042) Biography: Zou Xiu-fen(1996-), female, Ph. D candidate, Associate professor, research direction: evolutionary computing, parallel computing.     

The evolutionary computation techniques for protein structure prediction: A survey

In this paper, the applications of evolutionary al gorithm in prediction of protein secondary structure and tertiary structures are introduced, and recent studies on solving protein structure prediction problems using evolutionary algorithms are reviewed, and the challenges and prospects of EAs applied to protein structure modeling are analyzed and discussed. Foundation item: Supported by the National Natural Science Foundation of China( 60133010,70071042,60073043) Biography: Zou Xiu-fen ( 1966-), female, Associate professor, research direction:evolutionary computing, parallel computing, bioinformatics.     

Parameter optimization of electric bus transmission system based on dynamical evolutionary algorithm

The transmission ratio is the key parameters influence power performance and economic performance of electric vehicle (EV). As a class of heuristic algorithms, Dynamical Evolutionary Algorithm (DEA) is suitable to solve multi-objective optimization problems. This paper presents a new method to optimize the transmission ratio using DEA. The fuzzy constraints and objective function of transmission ratio are established for parameter optimization problem of electric bus transmission. DEA is used to solve the optimization problem. The transmission system is also designed based on the optimization result. Optimization and test results show that the dynamical evolutionary algorithm is an effective method to solve transmission parameter optimization problems.     

基于两个离散混沌动力系统的序列密码算法

基于两个离散混沌动力系统提出了一种新的序列密码算法.该算法用分段非线性映射的上一次迭代的输出作为分段非线性映射的下一次迭代的输入,并将迭代序列通过离散化算子转化为0-1序列,由0-1序列来选择两个混沌动力系统中的分段非线性映射.对算法进行了仿真实验和安全性分析,并对该映射产生的序列的随机性、初始值敏感性及其他性质进行了研究.研究结果表明,算法呈现出密钥、明文与密文之间高度的敏感性,密文和明文之间的相关度极小等特点,从而起到有效防止密文对密钥和明文信息泄露的作用.     

A hybrid model for the mid-long term runoff forecasting by evolutionary computation techniques

The mid-long term hydrology forecasting is one of most challenging problems in hydrological studies. This paper proposes an efficient dynamical system prediction model using evolutionary computation techniques. The new model overcomes some disadvantages of conventional hydrology forecasting ones. The observed data is divided into two parts: the slow “smooth and steady” data, and the fast “coarse and fluctuation” data. Under thedivide and conquer strategy, the behavior of smooth data is modeled by ordinary differential equations based on evolutionary modeling, and that of the coarse data is modeled using gray correlative forecasting method. Our model is verified on the test data of the mid-long term hydrology forecast in the northeast region of China. The experimental results show that the model is superior to gray system prediction model (GSPM). Foundation item: Supported by the National Natural Science Foundation of China ( 60133010, 70071042, 60073043) Biography: Zou Xiu-fen(1966-),female,Associate professor, research direction:evolutionary computing, parallel computing.     

基于异步动态系统的网络控制系统建模

研究了同时存在数据传输延时与数据包丢失的网络控制系统的建模问题．系统中传感器采用时间驱动，执行器与控制器采用事件驱动，传感器的数据采用单包传输．假设传输延时小于采样周期，且数据包传输的成功率一定，则整个网络控制系统可以描述为一个具有2个事件的异步动态系统．针对对象状态均可测，控制律采用状态反馈的情况，利用双线性矩阵不等式方法，讨论了网络控制系统指数稳定的问题，给出了稳定性的充分条件．     

非线性动力学方程的自适应精细积分

将定常结构动力方程的精细积分算法推广应用于非线性动力学问题的求解．对非线性项的线性化处理使该方法的计算精度对时间步长非常敏感,为此将龙贝格积分法引入该方法,提出了由此而产生的指数矩阵的快速精细算法,从而使时间步长的选择具有了自适应性,计算精度和效率均得到提高。     

动态系统的演化建模

针对传统方法解决动态系统微分方程建模问题所遇到的困难和存在的不足,设计将方程进行串结构编码并用进化方法进行演化建模的算法,以串形结构表示结构,用进化算法优化结构和参数,成功地实现了动态系统的常微分方程组建模过程的自动化。计算实例表明:采用此算法能够在极短的时间内由计算机自动发现多个较优的常微分方程组模型,与原来GA和GP结合的方法相比较,它具有建模过程智能化、模型结构非常灵活多样、数据拟合和预测精度更高等优点。     

基于蜜蜂进化型遗传算法的电力系统无功优化

采用蜜蜂进化机制与遗传算法相结合的蜜蜂进化型遗传算法(bee evolutionary genetic algo-rithm,BEGA)对电力系统进行无功优化计算.该算法以一定概率将蜂王(最优个体)与雄蜂(被选的个体)2部分进行交叉,因此对最优个体包含信息的开采能力得以增强.随机种群的引入,降低了算法出现过早收敛的可能性,保持了种群多样性.应用BEGA对IEEE6节点系统进行无功优化计算的结果表明:较其他算法,BEGA具有更强的全局寻优能力和更快的收敛速度.     

基于可变参数的混沌动力系统的序列密码体系

首先研究了一个混沌动力系统的统计性质,然后研究了将该动力系统进行平移变换后得到的一类新的混沌动力系统的统计性质,得到这两类动力系统具有相同的不变测度和均值,关于Lebesgue测度都是遍历的结论.还进一步给出了经平移变换后所得到的新的动力系统的相关函数的计算公式.最后利用带有平移参数的混沌动力系统给出序列密码加密与解密的算法,并进一步对算法进行了仿真实验和安全性分析,结果表明该算法加密效果良好,密钥、明文与密文之间关系均十分敏感,而且密文和明文的相关度也很小,具有很大的密钥空间和均匀分布的密文,可以有效地抵御统计分析,防止密文对密钥和明文信息的泄露,使系统具有很高的安全性.     

Parallel evolutionary modeling for nonlinear ordinary differential equations

We introduce a new parallel evolutionary algorithm in modeling dynamic systems by nonlinear higher-order ordinary differential equations (NHODEs). The NHODEs models are much more universal than the traditional linear models. In order to accelerate the modeling process, we propose and realize a parallel evolutionary algorithm using distributed CORBA object on the heterogeneous networking. Some numerical experiments show that the new algorithm is feasible and efficient. Foundation item: Supported by the National Natural Science Foundation of China (No. 70071042 and No. 60073043) Biography: Kang Zhuo (1970-), male, Lecturer, research interest: network computing and evolutionary computation.     

两输入非线性前馈系统的镇定方法

为了便于构造两输入非线性前馈系统的镇定控制器,通过变换构造出与原系统等价的复数域低维单输入非线性前馈系统,再利用已有的单输入系统的控制方法对该等价系统设计一个复数域镇定控制器,采用逆变换得到原系统的两个镇定控制器,提出了将原系统转化为等价系统后再进行设计的镇定方法。用Lyapunov稳定性定理证明了闭环控制系统状态的渐进稳定性。结果表明:等价系统比原系统具有更少的输入和更低的维数,基于等价系统的设计方法降低了系统的分析难度,简化了控制器的设计步骤。     

两输入非线性前馈系统的镇定方法

为了便于构造两输入非线性前馈系统的镇定控制器,通过变换构造出与原系统等价的复数域低维单输入非线性前馈系统,再利用已有的单输入系统的控制方法对该等价系统设计一个复数域镇定控制器,采用逆变换得到原系统的两个镇定控制器,提出了将原系统转化为等价系统后再进行设计的镇定方法。用Lyapunov稳定性定理证明了闭环控制系统状态的渐进稳定性。结果表明:等价系统比原系统具有更少的输入和更低的维数,基于等价系统的设计方法降低了系统的分析难度,简化了控制器的设计步骤。     

Cell evolutionary algorithm: a new optimization method on ground-state energy of the atomic

The purpose of this paper is to present a new general approach to solve ground-state energies of the double-electron systems in a uniform magnetic field, in which the basic element of evolution is the set in the solution space, rather than the point. The paper defines the Cell Evolutionary Algorithm, which implements such a view of the evolution mechanism. First, the optimal set in which the optimal solution may be obtained. Then this approach applies the embedded search method to get the optimal solution. We tested this approach on the atomic structure, and the results show that it can improve not only the efficiency but also the accuracy of the calculations as it relates to this specific problem. Foundation item: Supported by the opening Foundation of state key Laboratory of Magnetic Resonance and Atomic and Molecular physics, Wuhan Institute of physics, Chinese Academy of Science (981510) Biography: Liu Lian-jun(1946-), female, Associate professor, research direction: atom and molecular physics.     

Automatic evolutionary modeling by the Lattice-Boltzmann method

The Lattice-Boltzmann method is an effective tool for solving fluid mechanics problems, but there isn’t still a good scheme to determinate some parameters in Boltzmann equations. In this paper, a technique using evolutionary algorithm to automatically model Boltzmann equations is introduced. Numerical simulation shows that the designed scheme is fast and efficient. Biography: Chen Ju-hua ( 1963-), male, Associate professor, research direction: Lattice-Boltzmann method, evolutionary algorithm.     

求解非线性方程组的一种新方法及应用

针对非线性方程组求解问题提出一种变异量子粒子群算法,该算法首先把非线性方程组的求解转化为约束优化问题,然后根据可行性规则,引入约束违反度函数,结合变异算子,不断地寻找更优可行解,逐渐达到搜索全局最优解。数值实验表明,所设计变异量子粒子群算法是可行的、有效的,是求解非线性组的一种成功算法。     

一个随机动力系统中的中心极限定理

建立了一个适用于随机动力系统的特殊的中心极限定理.此定理是随机动力系统遍历理论中的一个新结果,可以用来分析某些双曲系统的随机轨道的分布,并进一步研究随机稳定性.     

并行求解非线性动力方程

研究非线性动力方程的并行求解问题, 利用幂级数展开法对非线性振动系统进行并行分析和运算, 并给出实例.     

非线性系统时变时滞和参数的在线联合估计

为了解决非线性系统的时滞和参数的在线联合估计这一问题 ,提出了一种基于遗传算法的非线性系统时变时滞和参数的在线联合估计方法。将遗传算法的二进制编码改进为十进制编码。对于系统输入带有纯时滞的非线性系统 ,采用改进的遗传算法对系统时滞和参数进行在线联合估计。此方法能够有效地在线联合估计非线性系统的时变时滞和参数 ,并具有一定的抗噪声能力。仿真实验结果验证了此方法的有效性     

带不确定动态输入非线性系统的鲁棒几乎干扰解耦

研究一类带不确定输入动态非线性系统的几乎干扰解耦问题 .利用反传设计方法构造了鲁棒状态反馈控制器 ,使得对所有可允许的不确定输入动态 ,闭环系统在零初始状态下从干扰到输出的L2 增益任意小 ,同时在干扰输入恒为零时闭环系统是全局渐近稳定的