Coordinated controller tuning of a boiler turbine unit with new binary particle swarm optimization algorithm

Coordinated controller tuning of the boiler turbine unit is a challenging task due to the nonlinear and coupling characteristics of the system. In this paper, a new variant of binary particle swarm optimization (PSO) algorithm, called probability based binary PSO (PBPSO), is presented to tune the parameters of a coordinated controller. The simulation results show that PBPSO can effectively optimize the control parameters and achieves better control performance than those based on standard discrete binary PSO, modified binary PSO, and standard continuous PSO.     

Performance assessment in an interactive call center workforce simulation

In this paper, a new performance assessment methodology for human-in-the-loop call center systems at the level of customer-agent interactions (CAI) is proposed. We develop a team-in-the-loop simulation test bed, to analyze CAI-level performance of a service system using a temporal performance measure with time windows. The proposed framework should allow researchers to collect and analyze individual as well as team performance at a finer granularity than current call center efforts which focus on queue-centered analysis. The software framework is object-oriented and has been designed to be configurable. A sample simulation study in different scenarios is illustrated to provide the usages and advantages of the proposed method with index of Interactive Service Performance.     

A quantitative sub-grid air entrainment model for bubbly flows - plunging jets

The accurate prediction of air entrainment is critical in simulating various important multiphase (air/water) flows. In this paper, we present a sub-grid air entrainment model that quantitatively predicts the rate of air entrainment and subsequent disperse bubbly flow for a plunging jet. The derivation of this model is based on the two-stage (i.e., low and high liquid jet velocity) air entrainment mechanisms suggested by Sene [Sene KJ. Air entrainment by plunging jets. Chem Eng Sci 1988;43(10):2615-23]. This model was validated against extensive experimental data for water jets in air over a wide range of liquid velocities (from around 1 to 10 m/s) for the total rate of air entrainment. It was then implemented into an Eulerian/Eulerian two-fluid computational multiphase fluid dynamics (CMFD) model, wherein the liquid and the bubbles are modeled as two distinct continua. This multiphase model, supplemented by the new sub-grid air entrainment model, was used to predict the void fraction distribution underneath plunging water jets at different depths and water jet velocities. It was found that this approach yields results that match the experimental observations very well.     

一类非完备信息博弈的信息模型

近年来随着对非完备信息博弈研究的不断深入,如何表示、处理博弈过程中的信息成了新的问题.提出了信息空间的概念,指出了信息集与信息空间的关系.首次采用二分图构建了Ⅱ型非完备信息游戏的通用信息模型,并在此模型基础上研究了信息获取方法,引入Markov模型进行信息处理.通过在四国军棋上的实验验证了通用信息模型在获取、管理非完备信息上的有效性,并证明了Markov网络在非完备信息处理中的有效性.     

一种支持大规模多种精度地形的实时绘制算法

为加强大规模地形数据的表现能力,通常采用地形叠加或地形编辑等方法在局部地形数据上构建更高精度的细节模型.因而如何将大规模地形数据与具有高精度的细节数据进行实时融合与绘制成为一个迫切需要解决的问题.基于Geometry Clipmap方法对这一问题开展研究,给出了一种支持大规模多种精度地形的实时绘制算法.在预处理阶段,对大规模地形数据采用clipmap结构进行组织,对细节数据使用mipmap结构进行组织;在运行阶段,重点针对clipmap更新所引起的不同种精度数据间特有的"F"形空洞进行分析和处理,使用过渡带结构对空洞区域进行修补,并对修补后的顶点进行了平滑处理.实验结果表明,该方法有效解决了"F"形空洞并支持大规模地形及细节数据的实时绘制.     

无线传感器网络中基于多属性决策的数据转发算法

如何在严格的能量约束下均衡传感器节点能耗、延长网络生存时间是无线传感器网络数据转发研究中的一个难题.利用多属性决策理论提出了一种基于多属性决策的数据转发(multiple attribute decision making based data forwarding, MadmDF)算法来解决该问题.MadmDF算法综合评价备选数据转发节点的属性信息,从中选择最优邻居节点进行数据转发,使网络数据流量得到了合理的分配,从而均衡了网络能耗,延长了网络生存时间.仿真结果表明该算法与同类数据转发算法相比具有一定优越性.     

基于最小平方误差逼近的线性阀体的设计

针对线性阀体的内孔筒设计问题,建立了一个以过流面积和其逼近直线之间的平方误差最小为目标的泛函优化模型.     

基于二进制搜索算法的RFID系统防碰撞算法

针对RFID系统中最常见的防碰撞问题,提出了一种基于二进制搜索的防碰撞算法.算法能动态调整指令发送长度和发送值,并在发生碰撞时,首先通过碰撞位中"1"的个数来识别标签.该算法能有效解决RFID系统中多目标识别的防碰撞问题.     

一种基于GIS动态服务技术的Agent迁移策略

针对现有分布式地理信息系统数据处理的瓶颈问题,利用Web服务和移动Agent技术解决GIS领域的动态服务问题,详细阐述GIS软件的系统结构和动态服务模型,介绍移动Agent和构件服务等相关实现技术,给出基于智能决策的Agent迁移策略及其算法描述.最后通过模拟仿真实验,验证了该迁移策略和算法的有效性.     

基于改进遗传算法的防空导弹分队WTA问题求解

针对以往防空作战中目标分配模型精度差、求解方法效率低的问题,建立了基于射击综合优势和目标威胁度的目标分配数学模型,其中目标威胁度评估综合运用了灰色综合关联度和改进的层次分析法,提高了结果的精度.并且采用改进的混沌蜜蜂双种群进化遗传算法对该模型进行了求解,改进的地方主要有:采用轮盘赌选择与最优保存策略相结合的选择操作,采用了算术交叉方法等.实验结果表明,应用文中的遗传算法求解防空导弹作战中目标分配问题,与传统算法相比,无论是在优化性能还是在时间性能上,都具有更好的效果.