基于改进CAPSO的原油管道调合多性质优化方法

在仔细研究原油管道调合工艺基础上,提出一种基于改进有约束自适应粒子群优化(CAPSO)算法的原油管道调合多性质优化方法;首先,基于原油调合规则库、优化预处理及设备实际工作能力约束,建立了多原油多性质优化模型;然后,根据原油调合目标,通过CAPSO算法对优化模型进行快速、准确的优化计算,获得多种组分原油的最优配比;投运效果表明,系统能够自动、高效计算出原油调合的最优配比,避免人工计算所造成的一致性差,计算效率低并且不易获得最佳配比的问题,有效提高了加工设备的生产效率。     

IBI and CA Model based Extraction of Urban Built\|up Areaand Its Application：A Case Study in Shanghai

At present,the automatic extraction of urban built\|up area is still a problem.Taking Shanghai city as an example,this research uses the binary image,which was derived from an IBI(index\|based built\|up index)image,as the geographical cellular automaton initial input data.This was then imported to the extended cellular automata model for further processing.After a series of processing such as thresholding,corrosion and connectivity test,the urban built\|up area was simulated and can be extracted.Based on this method,the urban built\|up area of Shanghai in five different years between 1987 and 2015 was extracted using multi\|temporal Landsat images of Shanghai.In addition,the urban growth intensity index,the concentric buffers analysis and radar chart analysis were calculated and used to analysis spatiotemporal pattern of Shanghai urban expansion in the 28 study years.The result shows that the built\|up area of Shanghai was expanded from 195 km² in 1987 to 1759 km² in 2015,which is eight times as large as that in 1987.In the period between 1987 and 2002,the urban built\|up area expanded mainly along the North\|South axis of the Huangpu River.However,after 2002 the expansion rate was increased more quickly,and the direction of the expansion was shifted to an east to west direction.Generally speaking,Shanghai has experienced a rapid urban expansion in the recent three decades.     

基于演化计算的异常轨迹并行检测算法

异常轨迹检测是轨迹数据挖掘研究领域的一个重要研究内容,基于演化计算的异常轨迹检测算法(Top-k evolving trajectory outlier detection, TOP-EYE)是一种有效的异常轨迹检测算法。不同于其他算法采用的轨迹距离计算方法,TOP-EYE算法 从轨迹的方向和密度角度出发,采用演化计算的方式检测异常。为了提高TOP-EYE算法对海量轨迹数据集异常检测的效率,本文在其基础上提出了基于MapReduce的异常轨迹检测并行算法(Parallel detecting abnormal trajectory based on TOP-EYE, PDAT-TOP ),利用MapReduce并行计算的优势提高了异常轨迹检测的效率。将算法PDA T-TOP在Hadoop平台上加以实现,实验结果表明,算法PDAT-TOP能够有效地检测异常轨迹,并且具有较高的可扩展性和加速比。     

新型人体参数自动测量系统

目的 针对国内外已有的非接触式测量系统普遍存在价格昂贵、安装复杂、占用空间大等问题,提出一种基于消失点和图像比例法相结合的人体参数尺寸的自动测量方法(HuFAMS-VP)。方法 首先,利用背景差分法,将人体从图像中分割出来;再将分割后的人体图像进行轮廓提取,从而获得人体轮廓图;然后,根据边缘检测和人体各个部位与人体身高比例等方法,获取人体几个关键部位特征点;最后,通过消失点方法(vanishing point)与比例法的结合获取人体参数尺寸。结果 根据HuFAMS-VP对7组被测人员(年龄在25±3岁,身高范围在1.7±0.2 m)进行尺寸测量,并与被测人员真实尺寸信息进行比较。由测量结果可以得到7组被测人员的绝对误差控制在±0.05 m之内,平均测量速度在2 s以内。结论 HuFAMS-VP在确保测量精度的前提下,具有操作方便、价格低廉等优势。根据测量结果,论证了本系统的准确性和鲁棒性。     

流程图化的嵌入式系统开发平台

面向嵌入式零代码基础使用者和低成本开发者,搭建了一个基于STM32的软硬件一体化编程的流程图化的嵌入式系统开发平台.该平台采用STM32作为硬件载体,用QT跨平台C++图形用户界面搭建简单易懂的流程图操作界面.硬件框图界面能驱动嵌入式设备,用编译软件封装功能模块放置功能编辑盒,通过命令行调用编译器,调用外部烧录软件完成下载,代码查看器可直观监视编译全过程.测试结果表明,该平台可方便、快捷解决编程问题.     

MT7620A平台与OpenWRT的WiFi通信系统设计

主要介绍一种在嵌入式平台上实现无线通信的方法,实现现场设备间的无线通信,同时,还具备将现场设备接入有线互联网的功能.在硬件平台上,本文选择在联发科芯片MT7620A上进行嵌入式开发,移植OpenWRT专业路由器系统,基于TCP/IP协议编写网络通信应用程序,实现网络数据到串口数据的透明传输.通过实物测试和NS-2平台无线通信仿真,对通信性能进行验证,并最后成功应用在现场中.     

自适应椭球包围盒改进织物碰撞检测方法

为了快速处理织物与模型的碰撞以获得仿真结果,提出一种基于自适应椭球包围盒的碰撞检测方法.该方法以法向距离和径向距离的加权平均值作为表面误差,数值化表示椭球与模型之间的拟合度,将优化K均值聚类方法用于自适应划分模型生成一系列逼近模型的最小体积包围椭球;根据表面误差的大小对椭球分类处理,误差小的椭球直接取代模型区域与织物碰撞,将三角网格之间的碰撞问题转化为质点相对于椭球的穿透测试,误差大的椭球与织物的碰撞检测仅用于排除不可能发生碰撞的三角形,再继续进行三角形之间的精确碰撞检测.实验结果表明,文中方法能快速、自适应地划分任意模型生成高度拟合的椭球,可大幅度地减少碰撞检测计算量,在提高计算速度的同时保证了仿真的真实感.     

An algorithm for automatic 2D finite element mesh generation with line constraints

In this study, an algorithm is designed specifically for automatic finite element (FE) mesh generation on the transverse structure of hulls reinforced by stiffeners. Stiffeners attached to the transverse structure are considered as line constraints in the geometry boundary. For the FE mesh generation used in this study, the line constraints are treated as boundaries and by that means the geometry domain attached to the line constraints is decomposed into sub-domains, constrained only by the closed boundaries. Then, the mesh can be generated directly on those sub-domains by the traditional approach. The performance of the proposed algorithm is evaluated and the quality of the generated mesh meets expectations.