一种基于遗传算法的语法网络搜索方法

本文以基于隐马尔科夫模型的语音识别系统为基线系统,提出了一种基于遗传算法的语法网络搜索方法,应用于语音识别系统的语法网络搜索模块。通过遗传算法解码得到的搜索结果虽然不唯一但都是满意解,提升了该模块的全局优化搜索能力。     

基于鱼群算法的全终端网络可靠性优化设计

鱼群算法是一种新型群智能优化方法,在分析鱼群算法实现原理的基础之上,将其与全终端网络可靠性优化问题有机融合,给出了求解全终端网络可靠性优化问题的鱼群算法设计.通过实例仿真比较,鱼群算法能够得到比遗传算法更满意的结果,从而验证了算法的可行性和有效性.     

计算机通信网络中容量与流量分配的优化研究

改进计算机通信网络中的流量与容量的分配问题,可以有效解决并降低计算机本身的运营费用。通过并行遗传算法,可以对计算机网络进行合理优化,除此之外,还可以将并行遗传算法与传统算法相比较,从而更清楚的了解到,哪种优化算法,可以更好的提高计算机网络运营质量。     

遗传算法在宽带IP网设计中的应用

讨论了使用遗传算法来进行宽带IP网络设计的研究方法，使用遗传算法对网络设计中的拓扑、路由和容量分配等方面的优化问题进行了详细的描述，并简要举例说明遗传算法的使用。     

一种基于自适应遗传算法的BP网络的应用

针对遗传算法和BP网络各自的优缺点，探讨了两算法结合的必要性、可能性以及结合方法，提出了一种改进的自适应遗传算法，并把该算法用于优化BP网络的权值。把经优化后的BP网络作为汉字识别的分类器，实验结果验证了所述方法的有效性。     

基于方程和遗传算法的CMOS模拟单元电路优化

本文在CMOS单元电路优化中采用一种基于方程和遗传算法的优化方法.其采用描述电路行为的性能解析方程和遗传算法实现电路性能指标的优化.仿真结果表明,这种方法可以得到满意的仿真结果,同时所需的优化时间较短.     

混沌遗传算法在配电网无功优化中的应用

配电网无功优化可以有效地降低网络有功损耗,并提高系统的电压合格率,从而降低网络年运行费用,提高供电质量。为了提高配电网无功优化的收敛速度,文中对常规的遗传算法进行了改进,利用混沌优化算法加速了适应值较低的个体的淘汰,提高了每一代个体的平均适应值水平,从而显著提高了常规遗传算法的收敛速度。通过实际算例计算,验证了该算法能有效地提高配电网无功优化的收敛速度和优化效果。     

基于并行遗传算法的神经网络在优化设计中的应用

利用并行遗传算法和Hopfield网络的优点，提出了采用遗传算法的并行搜索和解空间搜索的优点进行网络参数的选取，利用Hopfield网络简单、快速、规范的优点来优化样本空间，以取得整体的优化效率，从而解决复杂的优化问题。     

基于遗传算法的天线匹配网络研究

遗传算法是模拟生物进化过程而发展起来的一种优化和搜索求解极值问题的自组织、自适应的人工智能技术,其通过对一组编码进行简单的遗传操作和优胜劣汰来指导学习和确定进化的方向.遗传算法提供了一种求解非线性、多模型、多目标等复杂系统优化问题的通用框架.利用遗传算法针对天线匹配网络的设计进行研究,并利用安捷伦科技有限公司的ADS软件针对同一天线设计匹配网络,通过仿真结果证明利用遗传算法设计天线匹配网络的可行性与可靠性.     

基于遗传算法优化的WSN覆盖控制算法

针对无线传感器网络(Wireless Senson Networks,WSN)的覆盖控制和网络寿命问题,基于改进的遗传算法结合提出的局部搜索策略进行优化。根据WSN的特性对遗传算法的适应度函数进行了改进,并与提出的局部搜索策略结合进一步优化遗传算法适应度值,使之可以使用更少的传感器节点来保障监测目标的100%覆盖。仿真实验表明,与遗传算法相比,该算法具有更高的适应度、更长的100%覆盖期和网络寿命。基于遗传算法改进的WSN覆盖控制具有更优秀的性能及提高WSN对感知区域的覆盖控制能力。     

Reliability Optimization In The Design Of Telephone Networks

Telephone network reliability is defined as the degree of complying with subscribers expectations: the probability to have a given number of ready-to-use telephone channels between terminals. A model is presented for the cost minimization of an isolated telephone link, over capacity and channel reliability subject to reliability constraints. The optimization, achieved by Lagrange multipliers, results in a simple algorithm. The optimization of a link, belonging to a complex network, is reducible to the isolated link optimization problem.     

一种基于有序二元决策图和布尔函数性质计算网络可靠性的算法

有序二元决策图(OBDD)被广泛用到网络可靠度的计算中,在基于OBDD计算网络可靠度时,其计算时间主要取决于参与操作的OBDD的大小,而OBDD的大小严重依赖于OBDD的变量序。该文根据布尔函数的性质和OBDD原理提出一种优化计算网络可靠性的算法(BF-OBDD),提高计算网络可靠性的效率。实验结果表明改进的算法有较少的 OBDD节点数量,在计算网络可靠性时,花费的时间较少。     

基于联合备份的服务功能链可靠性保障的部署方法

在网络功能虚拟化(NFV)环境中,针对服务功能链(SFC)部署时的可靠性问题,该文提出对备份虚拟网络功能选择、备份实例放置和服务功能链部署的联合优化方法。首先,定义一个单位开销可靠性提高值的虚拟网络功能衡量标准,改进备份虚拟网络功能选择方法;其次,采用联合备份的方式调整相邻备份实例之间的放置策略,以降低带宽资源开销;最后,将整个服务功能链可靠性保障的部署问题构建成整数线性规划模型,并提出一种基于最短路径的启发式算法,克服整数线性规划求解的复杂性。仿真结果表明,该方法在优先满足网络服务可靠性需求的同时,优化资源配置,提高了请求接受率。     

Evaluation of optimal-reliability indices for electricaldistribution systems

A method to calculate the optimal values of reliability indices for a load point in an electrical distribution system is presented. The problem is formulated as an optimization problem and solved by the gradient projection method; the objective is to minimize interruption cost. The algorithm is very useful and powerful for extending the existing network and planning new networks. It has been tested on a practical system (the Port-Fouad power network), and the results are discussed. Once the optimal reliability indices are determined, modification of the system by equipment replacement and future system planning can be done in such a way that the interruption cost is minimized     

Reliability optimization models for embedded systems with multiple applications

Summary and Conclusions-This paper presents four models for optimizing the reliability of embedded systems considering both software and hardware reliability under cost constraints, and one model to optimize system cost under multiple reliability constraints. Previously, most optimization models have been developed for hardware-only or software-only systems by assuming the hardware, if any, has perfect reliability. In addition, they assume that failures for each hardware or software unit are statistically independent. In other words, none of the existing optimization models were developed for embedded systems (hardware and software) with failure dependencies. For our work, each of our models is suitable for a distinct set of conditions or situations. The first four models maximize reliability while meeting cost constraints, and the fifth model minimizes system cost under multiple reliability constraints. This is the first time that optimization of these kinds of models has been performed on this type of system. We demonstrate and validate our models for an embedded system with multiple applications sharing multiple resources. We use a Simulated Annealing optimization algorithm to demonstrate our system reliability optimization techniques for distributed systems, because of its flexibility for various problem types with various constraints. It is efficient, and provides satisfactory optimization results while meeting difficult-to-satisfy constraints.     

Reliability optimization of communication networks using simulated annealing

Two concepts of communication network reliability are considered. The first one, the ‘s-t’ reliability, is relevant for communication between a source station and a terminal station as in the case of a two way telephone communication. The second one, the overall reliability, is a measure of simultaneous connectedness among all stations in the network. An algorthm is presented which selects the optimal set of links that maximizes the overall reliability of the network subject to a cost restriction, given the allowable node-link incidences, the link costs and the link reliabilities. The algorithm employs a variaton of the simulated annealing approach coupled with a hierarchical strategy to achieve the gobal optimum. For complex networks, the present algorithm is advantageous over the traditional heuristic procedures. The solutions of two representative example network optimization problems are presented to illustrate the present algorithm. The potential utilization of parallel computing strategies in the present algorithm is also identified.     

Reliability and cost efficiency analysis for deep space habitat network based on Nash bargaining solution

Focusing on the deep space habitat network requirements of high reliability and expensive links,two impact factors to the network performance were regarded as a multi-objective optimization problem,which were network reliability and cost efficiency model,and the relations between the two factors were formalized.Thereafter,the Nash model of cooperative game was used to make a fairness compromise to the network reliability and cost efficiency,and the Nash bargaining solution set was acquired through the Matlab platform with CVX.Further,through changing the threat value dynamically and performing the repeated game,the Pareto optimal solution could be obtained which can ensure the fairness of reliability and cost efficiency simultaneously.Finally,the Nash bargaining method was applied to a typical deep space habitat network topology,and described in detail how to set up the link numbers and link capacity in order to reduce the cost when the network traffic and the link capacity were given.The proposed work is important for the deployment and optimization of the deep space habitat network.     

基于复合量度的电力光纤多电路配置可靠性

能源互联网的一个本质特征是通过先进的通信网络实现能源供给与消费间的双向互动。以光纤通信为基础的高可靠通信网络优化配置以满足多业务的服务质量(QoS)需求成为亟需解决的关键问题。从电力光纤传输网络的可靠性入手,并考虑电力通信业务的多QoS传输需求,设计一种基于复合量度的电路配置优化方法。有别于传统最短路配置算法,新方法在一次配置过程中同时规划m条可行配置方案,并且通过分析路径集的带宽、时延、丢包率、衰耗和成本等不同量度和光路全程可靠性,最终获得满足可靠性和传输QoS需求的光路配置方案,并给出优先选择序列。多电路优化配置将有效提升电力通信的可靠性,也可为未来多路流量分摊提供电路配置保证。通过某城区35~500 kV电力通信站网实例仿真计算,新配置方法能够一次获取4条同时满足业务多QoS需求的传输电路,实现主备电路保护。对电力光纤传输网络的规划和运行优化,提高电力通信网的资源调配能力和可靠性提供参考。     

基于改进灰狼优化算法的服务功能链映射算法

随着工业互联网、车联网、元宇宙等新型互联网应用的兴起，网络的低时延、可靠性、安全性、确定性等方面的需求正面临严峻挑战。采用网络功能虚拟化技术在虚拟网络部署过程中，存在服务功能链映射效率低与部署资源开销大等问题，联合考虑节点激活成本、实例化开销，以最小化平均部署网络成本为优化目标建立了整数线性规划模型，提出基于改进灰狼优化算法的服务功能链映射（improved grey wolf optimization based service function chain mapping，IMGWO-SFCM）算法。该算法在标准灰狼优化算法基础上添加了基于无环K最短路径（K shortest path，KSP）问题算法的映射方案搜索、映射方案编码以及基于反向学习与非线性收敛改进三大策略，较好地平衡了其全局搜索及局部搜索能力，实现服务功能链映射方案的快速确定。仿真结果显示，该算法在保证更高的服务功能链请求接受率下，相较于对比算法降低了11.86%的平均部署网络成本。     

Topological optimization of distributed computer networks subject to reliability constraints

A method of topological optimization of the networks with minimum cost subject to reliability constraints is given in this paper. The proposed optimization algorithm is based on branch and bound method. The computational results of this algorithm are discussed.