Introduction to Ant Colony Algorithm and Its Application in CIMS

Ant colony algorithm is a novel simulated ecosystem e volutionary algorithm, which is proposed firstly by Italian scholars M.Dorigo, A . Colormi and V. Maniezzo. Enlightened by the process of ants searching for food , scholars bring forward this new evolutionary algorithm. This algorithm has sev eral characteristics such as positive feedback, distributed computing and stro nger robustness. Positive feedback and distributed computing make it easier to find better solutions. Based on these characteristics...     

互补问题中Gauss-Newton方法全局收敛性的推广(英文)

研究了由Subramamian为求解互补问题提出的阻尼Gauss-Newton方法的收敛性质，在较弱的条件下，给出了一个全局收敛效果，这个结果是Subramanian PK (1993)和（1997）中相应结果的一个推广。     

利用二次贝齐尔函数的一维优化算法

本文利用贝齐尔函数良好的保型性质,将它作为拟合函数,构造了一个一维优化算法。数值实验表明,对于高度非线性的目标函数,新算法具有很强的适应性,比同类算法更有效。     

一个快速求解哈斯图的算法

在理论证明的基础上，给出了一个哈斯图求解的算法。该算法可直接应用关系图方便、快捷地求取其盖住关系，进而得到哈斯图，从而完善了有关哈斯图求解的理论及算法。     

变电站自动化系统中一种新智能测控装置设计

介绍了变电站自动化系统一种基于80C196KB控制CPU设计的新型线路单元测控装置。它能完成一条线路的遥测、遥信、遥控和遥脉功能。模拟量测量采用基于快速傅里叶变换的交流采样算法，测量精度高。与上位机的通信提供多种选择方式，人机交互采用点阵液晶显示及薄膜式键盘，开关量状态、脉冲量的采集以及控制输出都采用二次隔离技术，并采用了先进软件抗干扰技术，遥控操作可靠。     

容错控制器在破碎机调速系统应用中的仿真研究

针对单输入单输出多回路系统,采取一种简单的容错控制技术,当控制系统中任一传感器失效时,采用邻近回路重构控制律对水下破碎机转速控制器加以补偿,使控制系统仍能稳定且控制质量与传感器失效前相一致,并给出了其仿真结果.图6,参9.     

一个快速的二进制多重精度gcd算法

求两个整数的最大公因子（gcd)的经典的Euclid算法时间复杂度为O（ln^3n)，不适宜于多重精度运算。论文证明了gcd的相关性质，提出了一个基于二进制的、适用于多重精度运算的改进算法，其时间复杂度为O（ln^2n)。     

含有纯滞后对象的控制方法

评述纯滞后对象控制的两种典型方法─—大林算法和纯滞后补偿法的原理、优缺点、设计要求及存在问题，并讨论了两者的联系。     

Analysis of plane and axisymmetric flows of incompressible fluids with the stream tube method: Numerical simulation by trust-region optimization algorithm

New concepts for the study of incompressible plane or axisymmetric flows are analysed by the stream tube method. Flows without eddies and pure vortex flows are considered in a transformed domain where the mapped streamlines are rectilinear or circular. The transformation between the physical domain and the computational domain is an unknown of the problem. In order to solve the non-linear set of relevant equations, we present a new algorithm based on a trust region technique which is effective for non-convex optimization problems. Experimental results show that the new algorithm is more robust compared to the Newton-Raphson method.