Software-defined networking （SDN） is a generic term and one of the major interests of the telecoms industry （and beyond） over the past two years. However, defining SDN is a somewhat controversial exercise. The cla...Software-defined networking （SDN） is a generic term and one of the major interests of the telecoms industry （and beyond） over the past two years. However, defining SDN is a somewhat controversial exercise. The claimed flexibility, as well as other presumed assets of SDN, should be carefully investigated. In particular, the use of SDN to dynamically provision network services suggests the introduction of a certain level of automation in the overall network service delivery process, from service parameter negotiation to delivery and operation. This paper aims to clarify the SDN landscape and focuses on two main aspects of the SDN framework： net- work abstraction, and dynamic parameter exposure and negotiation.展开更多
This note deals with how to position bricks so that m aximizing the numbers of whole brick in a given area. A method by genetic algori thm is given to solve this problem. By this method, the numbers of whole brick a n...This note deals with how to position bricks so that m aximizing the numbers of whole brick in a given area. A method by genetic algori thm is given to solve this problem. By this method, the numbers of whole brick a nd their position are gained when given areas are convex polygon and brick is re ctangular, and you can easily design a CAD soft to optimize the scheme of positi oning bricks. It is huge advantage by this method when given areas are nonregula r. Some rules of parameter’s influence to algorithm are pointed out by computer simulation. The first section states the problem and the math model of problem is given out. The second section gives out the solution by genetic algorithm, in cluding description of genetic algorithm and steps of algorithm about proble m of positioning bricks. The third section gives a computer simulation example. The last section is some discussions about this algorithm, including the influen ce of parameter to algorithm and optimizing parameter. Some rule is gained.展开更多
文摘Software-defined networking （SDN） is a generic term and one of the major interests of the telecoms industry （and beyond） over the past two years. However, defining SDN is a somewhat controversial exercise. The claimed flexibility, as well as other presumed assets of SDN, should be carefully investigated. In particular, the use of SDN to dynamically provision network services suggests the introduction of a certain level of automation in the overall network service delivery process, from service parameter negotiation to delivery and operation. This paper aims to clarify the SDN landscape and focuses on two main aspects of the SDN framework： net- work abstraction, and dynamic parameter exposure and negotiation.
文摘This note deals with how to position bricks so that m aximizing the numbers of whole brick in a given area. A method by genetic algori thm is given to solve this problem. By this method, the numbers of whole brick a nd their position are gained when given areas are convex polygon and brick is re ctangular, and you can easily design a CAD soft to optimize the scheme of positi oning bricks. It is huge advantage by this method when given areas are nonregula r. Some rules of parameter’s influence to algorithm are pointed out by computer simulation. The first section states the problem and the math model of problem is given out. The second section gives out the solution by genetic algorithm, in cluding description of genetic algorithm and steps of algorithm about proble m of positioning bricks. The third section gives a computer simulation example. The last section is some discussions about this algorithm, including the influen ce of parameter to algorithm and optimizing parameter. Some rule is gained.
文摘为了提高辨识稳定图中真实模态的准确性与自动化程度,首先,从稳定点定义方式的角度论述了聚类算法效果欠佳的原因,并采用异阶系统非等权重的定义方式输出稳定点;其次,基于数据挖掘思想,采用改进的辨识聚类结构的有序点(ordering points to identify the clustering structure,简称OPTICS)算法自动清洗稳定点集,通过遍历性搜索的方式确定输入参数;然后,提出结合度矩阵去噪的自适应局部密度谱聚类(local density adaptive spectral clustering,简称SC-DA)算法分析稳定点集,并以簇中值作为模态参数的代表值,实现模态参数的自动化识别;最后,将含有密集模态的外滩大桥作为识别对象进行试验验证。试验结果表明:所提出方法具有较高的精度,与频域分解(frequency domain decomposition,简称FDD)法的频率结果最大相差仅为0.012 3 Hz,且在线识别的准确率达到82.86%,显著高于基于层次聚类的自动识别方法,实现了无人工干预下模态参数的自动、准确识别,具有一定的工程应用前景。
