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The method solves the limitation of converging to the local infinitesimal point in medical image segmentation,and adopts the initial algorithm to assure the initial searching scope of genetic algorithm which is better accommodable than standard genetic algorithm with fuzzy C-means clustering,speeding up the convergence of genetic algorithm.

算法除了解决模糊C均值聚类算法在医学图像分割中容易陷入局部最优解的问题,而且采用的初值化算法比标准的遗传模糊C均值聚类算法能确定更合适的遗传算法的初始搜索范围,从而加速了遗传算法的收敛过程。

And an on-line adaptative training algorithm of the weights of neuron is given, which enhances fusion precision of the model, fault tolerance and adaptive ability for subsystems 4 In order to diagnose the soft fault of integrated system, a new fault detection method is proposed based on federated filter, which can detect fault of system in short interval and greatly enhance the method sensitivity to fault A fault diagnosis method of Dynamically Tuned Gyro baesd on parameter estimation of kinetics model of rotor, and signal pretreatment, parameter estimation and strategy of fault identification are studied in detail The method can locate fault of DTG correctly and effectively, which provides a new approach and idea for gyro fault diagonsis 5 In order to diagnose the hard fault of integrated system, fault tree analysis is studied on fault disgnosis of integrated system circuits, and the hardware and software of disgnosis system are developed, with faults located to main module and circuit For futhur diagnosis, an optimal measurement technology in detection of circuits is discussed by improving an algorithm based on information theory, and a pratical method based on half-split method is proposed.

针对组合系统的软故障诊断问题,提出了基于联合滤波模型的一种新的故障检测算法,给出了算法的理论推导过程,该算法能在较短的时间内检测出系统故障,提高了算法对故障的敏感度;研究了基于动调陀螺转子动力学模型参数辨识的故障诊断方法,就其中的信号预处理、参数辨识及故障决策方法等关键技术进行了详细的研究,该方法可以正确、有效地检测与定位动调陀螺故障,为陀螺故障诊断提供了新的途径和思路。 5。针对组合系统的硬故障诊断问题,研究了基于系统浅知识推理的故障树法在组合系统电路子系统故障诊断中的应用,开发了相关诊断系统的软硬件,故障可定位到系统的主要功能模块和电路板级。为了进一步的故障定位,研究了电路板故障的最优检测问题,完善了基于信息理论的优化算法,并提出了基于&对分法&的一种实用的优化算法,故障可定位到电路板的主要功能元件级。在组建的SINS/GPS组合系统实验平台上,针对上述研究内容,进行了大量的实验研究。

The same result can also be achieved when optimizing F8 function (Rastrigin's function). Comparing to EGA, KEGA is easy to realize and the increase of computation load can be neglected, but the performance of KEGA can be improved greatly. 2. To enhance the speed of AIA, two new methods of computing the concentration of antibody were developed. Simulation results for F8 and F15 (needle in haystack: type I) functions show that the two methods can improve the running speed of AIA more than 8. 5 times. 3. As to the drawback in defining antibody concentration, a new definition based on Euclidean distance between two antibodies and fitness is proposed. On this basis, a new AIA was constructed. The convergence performance are more better than that of AIA. 4. Combining king crossover with AAIA and DBAIA, two new AIAs, KAAIA and DKBAIA, were proposed.

仿真实验结果表明KEGA实现简单,与EGA相比,其增加的计算开销可以忽略,但性能改善十分明显; 2、针对基于信息熵的免疫算法运行速度慢的缺点,提出了二种能够加快AIA运行速度的新的抗体浓度计算方法,得到两种新的免疫算法,即加速的人工免疫算法(Accelerated Artificial Immune Algorithm,AAIA)和加速的人工免疫算法-2(Accelerated Artificial Immune Algorithm-2,AAIA-2),对测试函数F15(needle in haystack:type I)、F8函数的仿真研究表明,这两种算法的运行速度都是AIA的8.5倍以上; 3、针对AIA的浓度定义存在的缺陷,提出了一种新的基于抗体间欧氏距离和适应度的新的抗体浓度定义,并依据该定义构造了一种基于欧氏距离的人工免疫算法(Euclidean Distance-based Artificial Immune Algorithm,DBAIA)。

A Multi-Species Cooperative PSO algorithm is developed using the ideas of species dividing in the bionomical world. The algorithm is shown to have guaranteed convergence to the global optimum. Furthermore, the training strategies of RBF network structures and weights based on the MCPSO aigorithm is proposed. Simulation results show that the algorithm is effective in such fields as chaotic time-sequence forecasting, system identification, speech signal processing and etc.

在分析基本微粒群算法和协同微粒群算法特点的基础上,借鉴生态学中的种群划分思想,设计出一种多种群协同进化微粒群算法,并分析了该算法的收敛性能;在分析径向基函数神经网络结构的基础上,提出了基于多种群协同进化微粒群算法的径向基函数神经网络结构和权值优化设计策略,并在混沌序列预测、系统辨识、语音信号处理等应用仿真实验中验证了算法的有效性。

An explicit definition of local peak is shown, and the existence condition of local peak is given. It is proved that the GA is constringent at the neighbor of its local peak. The theoretical evidences of some improvements on GA are given, which points out the way forward for improving GAs performance.

关于遗传算法的收敛性研究的一些典型结果包括:文献 [2 ]分析了在种群规模无穷的情况下典型遗传算法的收敛性;文献 [3]证明了典型遗传算法不收敛,而如果对算法采取记录每一代中最佳个体的策略,则改进的算法收敛;文献 [4]提出了一种等价的遗传算法,并给出了收敛条件与收敛速度;文献 [5 ]研

Hypercube has many advantages, such as smaller diameter, simple routing algorithm, many parallel paths between any two nodes, and fault-tolerance, on the other hand that the Hypercube nodal degree increased logarithmetically to the number of nodes has limited network population. So we propose a constant nodal degree hierarchical topology to remedy the weakness of Hypercube and take advantages of Hypercube most. Given the definition of FCCN we analyse the basic properties including nodal degree , number of links , extensibility and diameter (maximum network communication delay). Also we proposed a simple and self-routing algorithm applied in FCCN. Although the self-routing algorithm is not optimal, but at more than 82% case it can get the shortest path, and the percent is larger and larger increased with network levels. By the self-routing algorithm the internodal distance is calculated to evaluate the network communication delay more clearly. The average internal distance is in order of the cubic root of the network population that is almost same as logarithmetically relation in a few thousands. FCCN is a highly scalable network due to its recursive construction.

首先在比较了基本互连网络的基础上,看到超立体网络的杰出性能,包括网络直径小、寻路算法简单且为自寻路算法、容错能力好等等,但是由于其节点度随网络的规模的增加而按对数关系增长,使得超立体网络的应用规模受到极大限制,所以为了能最大限度利用超立体网络的优点的同时弥补其节点度方面的不足,作者提出了节点度等于常数4的FCCN网络结构,来最多地利用立方体网络的优点;然后在对FCCN网络进行严格的定义后,分析了网络的节点度、链路数、延伸特性、网络的直径(决定网络的最大通讯延迟)等,并提出了适于FCCN网络的简单的自寻路算法,计算自寻路算法可得到最短路径的比例,看到在多于82%以上的情况自寻路算法都是最优的,而且比例随网络层数的增加而增加;应用所提出的自寻路算法计算了可以更加准确反映网络通讯延迟的参数—网络平均节点距离,计算得到此参数与网络大小的立方根成正比,此比例关系在网络的规模在几千节点以内与对数关系的网络几乎一样;FCCN网络是一高度可扩展结构,这是因为FCCN的递归构成方式,使得网络在增加节点时其原有的拓扑结构可以保持不变,不需对网络进行重新设计,为网络的实用扩展提供了条件;理论分析得出FCCN网络是一种高度可扩展高性能网络的结论。

this text briefly introduce association rule.by analyzing the application of classic apriori algorithm, apriori algorithm is found that it has some disadvantages. and then farm_new algorithm and the apriori algorithm of riddling compression those improving the association rule algorithm are proposed.

简要地介绍了关联规则,通过对关联分析的经典算法-apriori算法的分析,发现了经典算法apriori算法的缺陷,给出了改进的关联规则算法farm_new算法和基于筛选压缩的apriori挖掘算。

Aiming at a typical complex electromechanical system—temper mill, the study takes its main driving control system as object of study, works out such a difficult problem that many parameters are coupled mutually, hard to be set and configurated in complex electromechanical system, and makes the performance goal of the control system be optimal in the adjustable ranges of parameters.

分析了遗传算法和模拟退火算法寻优性能和各自的不足与局限性,将两种算法巧妙地结合起来加以修正、取长补短构成新的退火遗传算法,提高了算法的整体寻优性能;并以典型的复杂机电系统—平整机为研究对象,以其主传动速度控制系统为切入点,应用退火遗传算法,解决了复杂机电系统中多参数、相互耦合、难于整定和组态的难题,使控制系统的性能指标在参数可调范围内达到最优。

On the base of the developments and the characteristics, a new commingled algorithm that is Probability Clonal Selection Particle Swarm Algorithm is put forward, and the application process of the commingled algorithm is presented after the commingled theory is analyzed.

接着,研究了算法的融合机理,并对各自的算法进行了改进,在改进的基础上,依据三种智能优化算法的特点,提出了一种新的融合算法,即概率克隆选择微粒群算法,并对其进行了理论分析,给出了融合算法的应用流程。

By using simulated annealing algorithm to mitigate the stress of culling in genetic algorithm and utilizing the Boltzmann mechanism of simulated annealing algorithm to control the acceptance of the individuals generated by copulated and varied, a CDMA multi-user detection method based on genetic annealing algorithm is adopted. The computer simulative experiment is conducted.

考虑到模拟退火算法和遗传算法各自的优缺点,将两者有效的结合起来,通过模拟退火算法来减轻遗传算法的选择压力,利用模拟退火算法的Boltzmann机制来接收交叉和变异后的个体,并且结合CDMA通信系统多用户检测的特点,采用了遗传退火算法对CDMA通信系统的多用户进行检测的研究。

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Since historical times,England ,where the early inhabitants were Celts, has been conquered three times .

从有历史以来,英国,在此地早期居住的是凯尔特人,已经被征服了三次。

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