网络信息两层过滤系统的设计

随着Internet的普及和应用,网络应用在人们生活中占据越来越大的比重,对网络中的信息进行实时过滤,具有十分重要的意义。本文对贪婪随机自适应算法(GRASP)进行扩展,得到基于权值的贪婪随机自适应算法(WGRASP),利用WGRASP、多模式匹配分类、支持向量机等算法构造了一个网络信息两层过滤系统。该系统能自动获取一个优良的非法关键词集合,且对网络信息的过滤具有较高的过滤速度和文本识别查准率、查全率。     

A generalization of the Curtis–Hedlund theorem

Let A be a set and let G be a group, and equip A^G with its prodiscrete uniform structure. Let τ:A^G→A^G be a map. We prove that τ is a cellular automaton if and only if τ is uniformly continuous and G-equivariant. We also give an example showing that a continuous and G-equivariant map τ:A^G→A^G may fail to be a cellular automaton when the alphabet set A is infinite.     

Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures

In this research, we work with data of futures contracts on foreign exchange rates for British pound (BP), Canadian dollar (CD), and Japanese yen (JY) that are traded at the Chicago Mercantile Exchange (CME) against US dollars. We model relationships between exchange rates in these currencies using linear models, feed forward artificial neural networks (ANN), and three versions of recurrent neural networks (RNN1, RNN2 and RNN3) for predicting exchange rates in these currencies against the US dollar. Our results on forecast evaluations based on AGS test the tests of forecast equivalence between any two competing models among the entire models employed for each of the series show that ANN and the three versions of RNN models offer superior forecasts for predicting BP, CD and JY exchange rates although the forecast evaluations based on MGN test are in sharp contrast. On the other hand forecast based on SIGN test shows that ANN and all the versions of RNN models offer superior forecasts for BP and CD in exception of JY exchange rates. The results for forecast evaluation for all the models for each of the series based on summary measures of forecast evaluations show that RNN3 model appears to offer the most accurate predictions of BP and RNN1 for JP exchange rates. However, none of the RNN models appear to be statistically superior to the benchmark (i.e., linear model) for predicting CD exchange rates.      

Decentralised control of chromatographic simulated moving bed processes based on wave front reconstruction

The behaviour of chromatographic simulated moving bed processes is described by the movement of concentration profiles through a circle of separation columns. A closed-loop control manipulates the profiles in order to meet demands concerning specified product purity and disturbance attenuation. If steep wave fronts of the concentration profiles occur, the controlled variables undergo fast changes in case of a transient of the process. In this case, a reconstruction of the wave fronts is necessary for a successful control.A simple and effective decentralised controller structure is proposed based on cascaded discrete-time PI controllers. On-line product purity measurements and the reconstructed wave fronts are used for control purposes. Two kinds of process models are used: a rigorous model for dynamic simulations, and strongly simplified plant models for the design of the wave front reconstruction and the controller. The latter models are identified based on experimental step tests with the reference plant and numerical simulations. The performance of the control system is evaluated by numerical simulations.     

A generalized autocovariance least-squares method for Kalman filter tuning

This paper discusses a method for estimating noise covariances from process data. In linear stochastic state-space representations the true noise covariances are generally unknown in practical applications. Using estimated covariances a Kalman filter can be tuned in order to increase the accuracy of the state estimates. There is a linear relationship between covariances and autocovariance. Therefore, the covariance estimation problem can be stated as a least-squares problem, which can be solved as a symmetric semidefinite least-squares problem. This problem is convex and can be solved efficiently by interior-point methods. A numerical algorithm for solving the symmetric is able to handle systems with mutually correlated process noise and measurement noise.     

一种具有双重进化空间的扩展粒子群优化算法

为了使粒子群优化(PSO)适于求解更多类问题,提出一种由动力空间和制导空间共同进化的改进粒子群优化算法-具有双重进化空间的扩展粒子群优化算法(简记EPSO).在EPSO中,在演化转换映射的作用下,首先将动力空间中对粒子辅助位置的进化转换为制导空间中对主导位置的进化,然后基于对主导位置的择优选择操作实现算法的进化过程.EPSO克服了PSO仅适于求解连续域最优化问题的缺陷,也非常适于求解离散组合优化问题.对于随机3-SAT问题、背包问题和TSP问题,通过与PSO、ACO和GA等算法的计算对比表明:EPSO是一种继承了PSO优点的高效、扩展演化算法.     

使用非均匀量化的Hough空间进行直线段检测

分析图像中最近邻直线间距离和夹角的非均匀性,得到这两个参数与线段方向和长度的相关关系,并由此提出了非均匀量化Hough空间的直线检测算法NUHT (Nonuniform Hough Transform).实验结果表明,NUHT在不降低运算效率的情况下,有2倍于标准Hough变换SHT (Standard Hough Transform)的直线段检测能力,同时误报率低于SHT的1/2.     

一种基于遗传算法的彩色图像分割改进算法

图像分割是进行图像理解的基础,也是图像工程技术中一个重要的问题.近几年来关于图像的分割方法层出不穷,但随着多媒体技术和Internet技术的发展,彩色图像分割处理的准确性和实时性要求也越来越高.为此提出了一种基于遗传算法的彩色图像分割改进算法.经过大量的对比实验表明,用这种方法分割目标和背景区域差别较大的彩色图像具有分割效果好、实时性、鲁棒性强的特点,是一种较为理想的分割方法.     

混合FSO/RF通信系统链路性能的研究

自由空间光通信可以提供快捷、经济的宽带访问,然而易受天气条件和传输距离限制。文章讨论了如何设计混合FSO/RF系统的链路,使之两种系统相互辅助,提高系统的有效性。链路恢复技术中的动态负载交换算法实现了FSO和RF间的负载交换,确保在不同传输损耗下的服务质量。     

论网站页面设计的一致性原则

随着网络技术与电子商务的发展,网站页面设计也越来越受重视,优秀的网页虽然各有特色,但都遵守最基本的原则即保证页面的一致性。通过从页面结构、色彩、导航栏以及页面标准元素功能四个角度分析应如何设计网站页面,既保证页面之间的一致性,又使得读者不会因页面风格过于一致而产生视觉疲劳,并在此基础上提出了一个基本的保证页面一致性的设计方法。