New Public Key Cryptosystems from Combinatorial Group Theory

0 IntroductionThe security of most commonly used cryptographicschemesis essentially based onthree families of compu-tational problems :the integer factoring problem(RSAprob-lem) ,the Diffie-Hell man problemand the discrete logarithmproblem,andthe elliptic curve variants thereof .Inthe middleof 1990s , Shor[1], Bonehet al[2]presented some remarkablequantumalgorithms which can solveinteger factoring problemand discrete logarithmproblemover any group including Ga-lois fields and elliptic curve…     

An Interval-valued Fuzzy Competitive Neural Network

Because interval value is quite natural in clustering, an interval-valued fuzzy competitive neural network is proposed. Firstly, this paper proposes several definitions of distance relating to interval number. And then, it indicates the method of preprocessing input data, the structure of the network and the learning algorithm of the interval-valued fuzzy competitive neural network. This paper also analyses the principle of the learning algorithm. At last, an experiment is used to test the validity of the network.     

SPHERE： a scalable multicast framework in overlay networks

This paper presents Sphere, a scalable multicast framework in overlay network. Sphere is a highly efficient, serf-organizing and robust multicast protocol overlayed on the Internet. The main contrihutions of this paper are twofold. First, Sphere organizes the control topology of overlay network in two directions： horizontal and vertical. The horizontal meshes are used to locate and organize hosts in tracks, and the vertical meshes are. used to manage the data paths between tracks. Second, Sphere balances stress and stretch of the overlay network by assigning hosts into different tracks and clusters. This structure distributes stress on the muhicast trees uniformly, and meantime makes path stretch as small as possible. Simulations results show that Sphere can support multicast with large group size and has good performance on organizing meshes and building data delivery trees.     

基于气测资料的储层含油气性识别方法

基于气测资料构造适当的综合指标，分别利用模糊模式识别和误差反向传播（BP）神经网络两种方法对储层含油气性进行了分析。结果表明，气测资料与储层含油气性具有较强的相关性。模糊模式识别方法可以用来确定气测综合指标与储层含油气性之间的模糊关系，而且对待识别样品气测资料的随机性具有较强的适应性；神经网络法能够较准确地建立气测综合指标与储层含油气性之间的非线性关系，但在待识别样品气测资料具有随机性的情况下，识别结果具有随机性：利用模糊模式和BP神经网络方法对储层含油气性进行识别具有一定的可行性，能快速为储层含油气性分析提供一定的参考依据，并且前一种方法的识别效果优于后一种方法。     

Password-Based Group Key Agreement Protocol for Client-Server Application

0 IntroductionWith the rapid advances of computer networks , moreand more users are connecting together to exchangelarge amounts of information and share useful resources .However ,the security issue is still a major gating factor fortheir full adoption; mainly due to many malicious adversariesresidingin networked environments will eavesdrop,interceptand modify the transmittedinformation.The client-server model , over past years , has enjoyedsignificant and continually increasing popularity in…     

基于模糊评价方法的中国水资源承载力研究

应用模糊综合评判方法对中国水资源承载能力进行了分析评价,探讨了水资源承载能力模糊综合评价的方法.在对水资源特征及开发利用等影响承载能力的主要因素进行分析的基础上,在评价因素选取、权重分配方面对水生态环境、生态用水因素给予了重点考虑.结果表明:中国西部地区水资源有较大的开发容量,水资源承载能力的潜力相对较大;长江、珠江流域及东部沿海地区用水紧张,水资源承载力基本枯竭.     

基于模糊聚类的PSO-神经网络预测热连轧粗轧宽度

为了提高热连轧粗轧宽度的控制精度,以攀钢热轧板厂实测数据为基础,采用粒子群优化算法训练神经网络并将其用于热连轧粗轧宽度预报,通过模糊聚类分析方法进行数据分析,科学选取学习样本,解决了由于样本多、学习速度慢的问题.实测数据运算表明,这种方法可避免神经网络陷入局部极小,带钢粗轧宽度的预报精度控制在6 mm以内,并且训练速度也有很大程度的改善,神经网络结构也得到优化,具有很大的应用潜力.     

基于粗糙集属性重要性的模糊聚类决策及应用

考虑到不同属性之间的重要性,利用粗糙集理论对模糊信息表或信息表中的不同属性之间(特别是定量属性与定性属性之间)进行耦合,提出一种计算不同属性间相似度的计算方法,即基于粗糙集属性重要性的模糊聚类方法,解决模糊信息表或信息表中属性值定量与定性描述并存情况下的聚类问题,并根据原类结果建立决策表.     

经济全球化进程中的软实力与传统文化的发扬——析"和谐世界"

中国传统文化源远流长,代代相传.它是几千年中国社会发展的思想动力,也是今天中国提出构建“和谐世界“理念的思想源泉.在经济全球化曲折发展的当今时代,在不同民族和地域的文化特点与差异依然存在的情况下,减少摩擦、增加共识.发扬“和为贵“、“和而不同“的思想显得更为重要.“和谐世界“思想既是对中国文化与外来文化千年交往史的经验总结,也是将中华文化中的精髓向世界做郑重推荐,更是提升了中国的软实力.     

基于遗传算法的电梯群控鲁棒优化模型

针对电梯群控调度过程中交通流不确定的问题,建立了鲁棒优化模型,利用遗传算法对所建模型进行求解.对于不确定线性优化问题,研究了不确定集的选择以及模型鲁棒对等式转化方法.仿真实验中,利用电梯群控虚拟仿真环境对鲁棒优化调度算法在不同交通流下进行了验证.以300人/15 min的混合交通流模式为例,鲁棒优化算法的平均候梯时间比静态分区算法降低12.77 s;平均乘梯时间比最小等待时间算法降低9.7 s;电梯启停次数比静态分区算法少8次.实验结果表明,鲁棒优化调度算法对不同交通模式具有更好的适应性,可以减小交通流不确定性的影响,提高电梯群控调度性能.