Disaster Monitoring of Satellite Image Processing Using Progressive Image Classification

The analysis of remote sensing image areas is needed for climate detec-tion and management,especially for monitoringflood disasters in critical environ-ments and applications.Satellites are mostly used to detect disasters on Earth,and they have advantages in capturing Earth images.Using the control technique,Earth images can be used to obtain detailed terrain information.Since the acquisi-tion of satellite and aerial imagery,this system has been able to detectfloods,and with increasing convenience,flood detection has become more desirable in the last few years.In this paper,a Big Data Set-based Progressive Image Classification Algorithm(PICA)system is introduced to implement an image processing tech-nique,detect disasters,and determine results with the help of the PICA,which allows disaster analysis to be extracted more effectively.The PICA is essential to overcoming strong shadows,for proper access to disaster characteristics to false positives by operators,and to false predictions that affect the impact of the disas-ter.The PICA creates tailoring and adjustments obtained from satellite images before training and post-disaster aerial image data patches.Two types of proposed PICA systems detect disasters faster and more accurately(95.6%).

Continuities of Progressive and Mixing Algorithm for Surface Modeling and Editing

The progressive and mixing algorithm(PAMA) is a method for surface modeling and editing,which is developed for effective and flexible applications in many environments,such as computer-aided design(CAD) and computer-aided geometric design(CAGD).In this paper,the construction scheme and continuities of PAMA are discussed,which provide a mathematics analysis of PAMA.The analysis and results show that the PAMA provides a new method of surface modeling and editing with four more degrees of freedom for designers to manipulate a 3D object.

无线传感器网络的ProgressiveSkyline连续查询

随着传感器技术的进步,无线传感器网络支持复杂查询在现实应用中越来越重要。Skyline查询由于可用于多种标准下的决策而受到广泛关注。对无线传感器网络中Skyline连续查询进行了研究,提出了一种增量(progressive)算法来解决静态数据集中的Skyline查询求解问题,这种增量算法能够递增返回Skyline结果,而无需事先扫描整个数据集。设计了一种新颖的算法来解决流数据集中的Skyline查询维护问题。通过实验对算法性能进行了验证,结果表明,该算法能够大大延长网络的生命周期。

Progressive failure processes of reinforced slopes based on general particle dynamic method

In order to resolve grid distortions in finite element method(FEM), the meshless numerical method which is called general particle dynamics(GPD) was presented to simulate the large deformation and failure of geomaterials. The Mohr-Coulomb strength criterion was implemented into the code to describe the elasto-brittle behaviours of geomaterials while the solid-structure(reinforcing pile) interaction was simulated as an elasto-brittle material. The Weibull statistical approach was applied to describing the heterogeneity of geomaterials. As an application of general particle dynamics to slopes, the interaction between the slopes and the reinforcing pile was modelled. The contact between the geomaterials and the reinforcing pile was modelled by using the coupling condition associated with a Lennard-Jones repulsive force. The safety factor, corresponding to the minimum shear strength reduction factor "R", was obtained, and the slip surface of the slope was determined. The numerical results are in good agreement with those obtained from limit equilibrium method and finite element method. It indicates that the proposed geomaterial-structure interaction algorithm works well in the GPD framework.

基于Progressive多序列比对方法的求解多序列比对的启发式算法

在生物信息学研究中,生物序列比对问题占有重要的地位。多序列比对问题是一个NPC问题,由于时间和空间的限制不能够求出精确解。文中简要介绍了Feng和Doolittle提出的多序列比对算法的基本思想,并改进了该算法使之具有更好的比对精度。实验结果表明,新算法对解决一般的progressive多序列比对方法中遇到的局部最优问题有较好的效果。

Bayesian Inference on Type-Ⅰ Progressively Hybrid Competing Risks Model

In this paper, we construct a Bayesian framework combining Type-Ⅰ progressively hybrid censoring scheme and competing risks which are independently distributed as exponentiated Weibull distribution with one scale parameter and two shape parameters. Since there exist unknown hyper-parameters in prior density functions of shape parameters, we consider the hierarchical priors to obtain the individual marginal posterior density functions,Bayesian estimates and highest posterior density credible intervals. As explicit expressions of estimates cannot be obtained, the componentwise updating algorithm of Metropolis-Hastings method is employed to compute the numerical results. Finally, it is concluded that Bayesian estimates have a good performance.

PRECESION： progressive recovery and restoration planning of interdependent services in enterprise data centers

The primary focus of this paper is to design a progressive restoration plan for an enterprise data center environment following a partial or full disruption. Repairing and restoring disrupted components in an enterprise data center requires a significant amount of time and human effort. Following a major disruption, the recovery process involves multiple stages, and during each stage, the partially recovered infrastructures can provide limited services to users at some degraded service level. However, how fast and efficiently an enterprise infrastructure can be recovered de- pends on how the recovery mechanism restores the disrupted components, considering the inter-dependencies between services, along with the limitations of expert human operators. The entire problem turns out to be NP- hard and rather complex, and we devise an efficient meta-heuristic to solve the problem. By considering some real-world examples, we show that the proposed meta-heuristic provides very accurate results, and still runs 600-2800 times faster than the optimal solution obtained from a general purpose mathematical solver [1].

算法推荐技术赋能青少年民族团结进步教育的逻辑理路、价值意蕴与实践路径

算法推荐技术是引领新时代青少年民族团结进步教育高质量开展的新兴力量。算法推荐技术与青少年民族团结进步教育在条件、过程、结果上的关联耦合,为充分发挥算法推荐技术的积极功能,提升青少年民族团结进步教育实效,提供了适切性与可行性。通过精准传递、精准生产、精准过滤等优势赋能,算法推荐技术可以助力青少年民族团结进步教育实现对象大众化、内容智慧化和方式生活化。深化算法推荐理念认识、加强算法推荐素养教育、健全算法推荐技术规范,可以促进算法推荐技术势能充分释放,使之成为青少年民族团结进步教育现代化的强大技术支撑。

面向栅格地图的区域渐进均分算法

单架无人机续航能力限制了区域全覆盖侦察,合理的区域划分是实现多无人机协同全域侦察的关键。栅格法规划侦察区域是无人机区域侦察的常用研究方法。为了解决栅格地图等量划分的问题,提出了一种面向栅格地图的区域渐进均分算法。算法由4个阶段构成。阶段1,建立区域边界确认的跳跃迭代法,根据栅格的特点制定判定条件,进行栅格特征标识。阶段2,提出一种双特征标识方法,对射线法进行改进,确定区域内部栅格。阶段3,模仿水波扩散,提出了一种邻边扩散法,实现区域初步的扩散分割。阶段4,设计补偿规则,通过邻边补偿算法,对各子区域栅格数进行数量补偿。实验证明,区域渐进均分算法相较于其他算法,具有较好的聚集性,连续性和均匀性,为多无人机协同全域侦察提供了理论保证。

数字乡村建设赋能县域经济高质量发展研究——基于技术进步偏向视角

利用全国1869个县域数据,基于新发展理念构建指标体系,采用随机森林算法测度并描述全国县域高质量发展水平,并进一步从技术进步偏向的视角分析数字乡村建设赋能县域高质量发展的效应和机制。研究发现:第一,中国县域高质量发展水平稳步提高,综合指数均值整体呈现波动上升趋势,且存在着显著的全局空间集聚效应和地域差异,障碍因素诊断发现创新相较于其他四个维度障碍度的比例较大。第二,数字乡村建设能够显著促进中国县域的高质量发展。第三,技术进步偏向在数字乡村建设对中国县域高质量发展的影响中发挥中介作用。具体而言,数字乡村建设能够加快促进中国县域技术进步发生由劳动偏向型向资本偏向型的转变,并进而增加县域创新产出来显著推动中国县域经济高质量发展。因此,应继续强化数字赋能,引导资本更多向县域流动,强化技术进步的资本偏向,以发挥数字乡村建设赋能县域高质量发展的作用。

基于粒子群算法的复杂山区铁路土方调配与取弃土场选址协同优化

复杂山区铁路线路土方调配及取弃土场选址对铁路项目的成本、工期、安全性、环境影响程度等产生长久深远影响,二者之间存在着复杂关联耦合关系。然而,既有方法忽略了上述联系,难以实现铁路线路土方调配与取弃土场选址协同优化。对于复杂山区铁路线路,构建了融合调配段落划分点、土方调配量、取弃土场的统一自变量集合,考虑了土方调配、取弃土场选址复杂约束,以土方调配成本、取弃土场建设成本及便道建设成本的综合费用为目标函数,集成综合基础信息子系统、土方调配优化子系统与取弃土场选址优化子系统,建立了土方调配与取弃土场选址的协同优化模型。为求解此协同优化模型,提出一种基于粒子群算法的累进求解策略。首先根据线路划分土方调配段落,进入土方调配优化子系统求得土方调配解,借助移动窗口法构建取弃土场备选池,进入取弃土场选址优化子系统求得取弃土场址解;其次,基于粒子群算法通过更新线路土方调配段落划分来累进迭代寻求最优解。以某复杂山区铁路为例,对铁路线路土方调配及取弃土场选址协同优化模型进行案例验证,与人工方案相比,最终机选最优方案可节省13.77%的综合费用。测试结果表明本方法的有效性,可提高铁路土方调配与取弃土场选址求解效率,为设计人员提供参考。

Fast algorithm for constructing neighbor-joining phylogenetic trees

To improve the performance of Saitou and Nei＇s algorithm （SN） and Studier and Keppler＇s improved algorithm （SK） for constructing neighbor-joining phylogenetic trees and reduce the time complexity of the computation, a fast algorithm is proposed. The proposed algorithm includes three techniques. First, a linear array A[N] is introduced to store the sum of every row of the distance matrix （the same as SK）, which can eliminate many repeated computations. Secondly, the value of A [i] is computed only once at the beginning of the algorithm, and is updated by three elements in the iteration. Thirdly, a very compact formula for the sum of all the branch lengths of operational taxonomic units （OTUs） i and j is designed, and the correctness of the formula is proved. The experimental results show that the proposed algorithm is from tens to hundreds times faster than SN and roughly two times faster than SK when N increases, constructing a tree with 2 000 OTUs in 3 min on a current desktop computer. To earn the time with the cost of the space and reduce the computations in the innermost loop are the basic solutions for algorithms with many loops.

含缺陷C/C-SiC缎纹编织复合材料的压缩损伤及失效机制

为了研究含孔隙缺陷缎纹编织复合材料的压缩力学性能和失效机制,开展了含孔隙C/C-SiC缎纹编织复合材料的经向压缩实验;通过基于离散单元法的爆炸碎片算法来引入随机孔隙,建立了含孔隙缺陷缎纹编织复合材料的细观强度预测模型。基于该模型模拟了经向压缩载荷下细观模型的渐进失效过程,揭示了孔隙对损伤过程的影响规律,结合实验数据对渐进损伤过程和失效机制预测模型进行了验证。结果表明,在经向压缩载荷下材料主要破坏模式为剪切破坏和分层破坏,具体表现为三种形式:层间局部基体开裂、基体与经纱脱粘后分层,经纱整束断裂、部分断裂,以及纬纱脱粘与基体分离、纬纱开裂。同时数值模拟结果与实验值基本相同,验证了该含孔隙缺陷C/C-SiC缎纹编织复合材料模型的有效性,为二维编织复合材料的力学性能研究提供了一种有效方法。

弱特征表面形貌测量的低成本渐进式匹配方法

弱特征连续表面的匹配问题是计算机视觉和图像处理中的一个挑战性问题,基于标准夹具的特征辅助可以准确地实现测量数据与模型的匹配,但该方法成本较高。针对该问题,提出了一种低成本的渐进式的匹配算法,首先基于带有边界罚函数的“点到面”ICP算法实现粗配准,接着通过对测量数据进行两步微调即可对标工业常用评价结果。以汽车玻璃的面形误差评价为例,仿真和实验结果表明,基于所提方法匹配后的面形误差接近传感器本身的误差级别。对于40 cm×40 cm的汽车玻璃,基于所提方法匹配线结构光测量的玻璃数据与三坐标数据,两者偏差在-0.06/0.08 mm,基本满足工业需求。

基于云边协同的工程施工进度智能全时空监控软件设计与实现

基于目标检测优化的深度学习算法,研发了一套基于云边协同的工程施工进度智能全时空监控软件。该套软件包括边缘进度采集装置和云端进度智能监控软件后台。施工现场部署边缘进度采集装置,装置内构建了精细化训练网络算法模型,选取38类关键识别对象,建立了输变电工程现场基建的构建筑物样本库,工程进度识别准确率提升达到96%以上。同时,边缘进度采集装置将进度数据实时上传汇聚至云端的进度智能监控软件后台,后台整合现场班组人员、设备资源投入等全要素信息,建立工程进度风险分级预警模型,通过识别出的多维数据的协同分析,实现基建现场进度精准预警掌控,解决了输变电工程的进度管控困难问题。

基于混合威布尔分布的应力-强度模型可靠度估计

为了获得产品完全的故障数据和相对准确的可靠度,在逐步Ⅰ型区间删失下,假设应力和强度变量相互独立,应力变量服从一个Lindley分布,强度变量服从混合威布尔分布,构建应力-强度模型进行可靠度估计。首先,运用EM算法和Bootstrap方法分别推导得到模型可靠度R的极大似然估计和区间估计,再基于Monte-Carlo模拟及实例数据,运用上述方法对模型的可靠度估计进行分析。结果表明,在偏差意义下,随着样本量的增加,混合威布尔的可靠度估计值逐渐接近真实值。同时,运用混合威布尔分布和单一威布尔分布对Monte-Carlo模拟及实例数据进行拟合分析。结果显示,在AIC信息准则下,混合威布尔分布拟合效果优于单一威布尔分布。

机载LiDAR点云数据的组合滤波算法研究

针对采用渐进式形态学滤波算法进行机载LiDAR点云滤波时存在的滤波效果不佳、地形特征保留不明显的问题,本文提出了一种改进不规则三角网的后处理滤波算法,构建组合式机载LiDAR点云滤波算法。该组合算法有效地结合了渐进式形态学滤波算法与改进TIN滤波算法的优势,首先采用渐进式形态学滤波算法对原始机载LiDAR点云数据进行处理,提取得到初始地面点;其次优化传统TIN滤波算法,以初始地面点及种子点构建TIN,通过连续迭代提取得到精细化地面点。为验证本文提出滤波算法的可靠性与优越性,选取宁波市某地2组机载LiDAR点云数据进行实验,结果表明,与较单一的渐进式形态学滤波算法、TIN滤波算法地面点提取结果相比较,本文改进滤波算法提取地面点的Ⅰ类误差、Ⅱ类误差及总误差均更低,且不受地形条件限制,具有较高的适应性,验证了本文提出改进滤波算法的可靠性与优越性。

基于递进优化算法的城市轨道交通网络末班车换乘优化研究

城市轨道交通在城市公共交通体系中占重要地位,随着其客运分担率的持续上升,优化网络末班车换乘成为提升乘客出行体验与资源配置效率的关键。文章提出一种基于递进优化算法的网络末班车换乘优化方法,该方法通过末班车换乘优化算法、延长换乘站停站时间的扩大优化算法和回场车临时载客的末班车换乘优化算法层层递进,从单向换乘衔接转变为双向换乘衔接,以实现换乘量的最大化。为验证该方法的有效性,以石家庄市轨道交通为例进行实证研究。结果表明,基于递进优化算法的网络末班车换乘优化方法不仅适应性强,而且具有高度的可实践性,对于提升城市轨道交通运营效率和服务质量具有重要意义。

车辆自适应巡航下的MPC方法的研究

提出了一种新颖的车辆自适应巡航控制(ACC)系统,该系统可以在保障跟车距离的同时,提升车辆的燃油经济性。基于模型预测控制(MPC)进行ACC的上层控制器搭建,并在此基础上采用高斯过程回归(GPR),网格搜索(GS)和自适应方法进行三轨参数调整,将控制域和预测域调整到最优状态。此外,为了减少计算量并提高稳定性,系统采用了粒子群优化算法(PSO)对系统进行升级改进。仿真结果表明,基于MPC控制的车辆自适应巡航控制系统可以在保证良好跟踪性能的同时降低燃油消耗率。

逐步Ⅱ型删失下Burr Type X分布的参数估计

针对逐步Ⅱ型删失数据下Burr Type X分布的参数估计问题,提出模型参数的一种新的贝叶斯估计及相应的最大后验密度(HPD)置信区间.假设伽玛分布为待估参数的先验分布,考虑待估参数的条件后验分布未知、单峰且近似对称,选取以正态分布为提议分布的Metropolis-Hastings(MH)算法生成后验样本,基于后验样本在平方误差损失函数下得到待估参数的贝叶斯估计和HPD置信区间.将基于MH算法得到的贝叶斯估计和HPD置信区间与基于EM算法得到的极大似然估计和置信区间在均方误差准则和精度意义下进行比较.Monte-Carlo模拟结果表明,基于MH算法得到的估计在均方误差准则下优于基于EM算法得到的极大似然估计,基于MH算法得到的HPD置信区间长度小于基于EM算法得到的置信区间长度.