移动轨迹聚类方法研究综述

轨迹数据是人类移动行为的表征,能够映射出人的出行模式和社会属性等信息。怎样有效挖掘轨迹数据蕴藏的人类活动规律一直是研究的热点。通过轨迹聚类发现行为相似的类簇,从而探究群体的移动模式是轨迹挖掘和深度应用常见的方法之一。本文首先根据轨迹数据的特点,将轨迹数据模型分为轨迹点模型和轨迹段模型,并据此定义相应的相似性度量：空间相似性度量和时空相似性度量;然后,对两类模型的聚类方法进行了综述,并总结不同聚类算法的优缺点,以期为不同应用选取聚类算法提供科学依据;最后对移动轨迹数据聚类方法研究的发展趋势进行了讨论。     

室内用户语义位置预测研究

位置预测技术可以提前预知用户下一时刻的位置,在基于位置的服务（Location-based Service,LBS）领域中发挥着极其重要的作用。现有的位置预测技术大多仅使用用户的地理轨迹,仅使用地理轨迹挖掘出来的用户移动模式易受地理特性的限制缺乏深层次的语义信息。本文基于某商场群体用户的室内轨迹数据和语义信息预测用户下一个时刻语义位置。语义位置预测包括停留区域识别、停留区域语义匹配、语义位置建模。在停留区域识别阶段,为减少室内停留时间不固定对停留区域识别的影响,本研究提出了一种新型的时空凝聚层次聚类算法（Spatial-Temporal Agglomerative Nesting, ST-AGNES),该算法具有思想简单、超参数少、自动生成聚类个数等优点。在语义匹配阶段,引入了吸引度规则,充分利用停留区域所有轨迹点与室内高密度的商铺名称信息做匹配。最后,采用长短型记忆神经网络模型（Long Short-Term Memory,LSTM）挖掘群体用户的语义位置模式并预测用户未来的语义位置,实验预测正确率达到61.3%。     

海上油田开发井钻井优化设计和应用实践

LF7-2油田位于我国南海珠江口盆地LF区块,是一个小规模油田,根据前期探井揭示,上部地层以厚层泥岩为主,极易水化、分散,使钻井液性能变差;起下钻过程中钻具遇卡、遇阻等复杂情况频繁发生;钻头选型不尽合理,易泥包;下部地层以砂泥岩互层为主,岩石致密、可钻性变差,钻具扭矩、摩阻增加,定向钻进时滑动困难,井眼轨迹控制难度大,给钻井提速增效带来诸多困难。根据探井地质情况和岩石力学剖面,利用钻井软件优选平台位置,对开发井井身结构、井眼轨迹、钻柱力学、钻井液、固井等方面进行钻井仿真模拟,制定出科学的钻井设计方案,在直井段采用“牙轮钻头+直螺杆+MWD”钻具开展防斜打直,造斜段使用“PDC钻头+弯螺杆+MWD/LWD”开展复合钻井,水平段采用“PDC钻头+PowerDriver+MWD/LWD”开展旋转导向钻井,实现精准化钻井,顺利完成6口开发井施工。现场应用单井平均机械钻速29.43 m/h,钻井工期191.59 d,工期比设计提前28.41 d,钻井提速增效显著,降低开发成本。通过PowerDriver的近钻头井斜、自然伽马实时测量和传输,减少地质误判,实现对储层顶界面的实时探测,使储层钻遇率达100%,收到较好的经济效益和投资回报,实现小油田的效益开发。     

MARC: a robust method for multiple-aspect trajectory classification via space,time, and semantic embeddings

ABSTRACT

The increasing popularity of Location-Based Social Networks (LBSNs) and the semantic enrichment of mobility data in several contexts in the last years has led to the generation of large volumes of trajectory data. In contrast to GPS-based trajectories, LBSN and context-aware trajectories are more complex data, having several semantic textual dimensions besides space and time, which may reveal interesting mobility patterns. For instance, people may visit different places or perform different activities depending on the weather conditions. These new semantically rich data, known as multiple-aspect trajectories, pose new challenges in trajectory classification, which is the problem that we address in this paper. Existing methods for trajectory classification cannot deal with the complexity of heterogeneous data dimensions or the sequential aspect that characterizes movement. In this paper we propose MARC, an approach based on attribute embedding and Recurrent Neural Networks (RNNs) for classifying multiple-aspect trajectories, that tackles all trajectory properties: space, time, semantics, and sequence. We highlight that MARC exhibits good performance especially when trajectories are described by several textual/categorical attributes. Experiments performed over four publicly available datasets considering the Trajectory-User Linking (TUL) problem show that MARC outperformed all competitors, with respect to accuracy, precision, recall, and F1-score.     

江苏盐城地区一次持续雾-霾天气过程的综合分析

2013年12月上旬江苏盐城地区出现了一次历史罕见的持续重度雾-霾天气,利用盐城市常规气象观测资料、NCEP再分析资料(1°×1°)及环境监测中心站的污染物浓度资料等,对此次过程的环流背景、气象要素、大气层结特征以及动力条件、污染情况等进行了综合性分析。结果发现:12月上旬中高层冷空气势力弱,以纬向环流为主;低层弱的水平风场为雾-霾的发生发展提供了有利的环流背景;稳定的层结特征,近地面高强度的贴地逆温和持续较低的混合层高度是此次雾-霾天气长时间维持的重要因素;边界层内弱正散度及负涡度是此次雾-霾天气得以维持发展的动力因子;通过后向轨迹分型和火点监测资料分析发现:污染物的长距离输送在此次重污染天气的形成过程中起到了一定作用。最后,文中建立了能见度和PM_(2.5)浓度、相对湿度的非线性回归方程,对能见度的预报效果较好,为实际业务应用中雾-霾的预报提供了有利的依据。     

热带气旋“Malakas”与中纬度系统的相互作用及其结构变化

本文利用中尺度数值模式WRF和LAGRANTO轨迹模式对2010年变性台风"Malakas"进行数值模拟和轨迹分析,分析了Malakas在变性过程中与中纬度系统的相互作用,以及在相互作用过程中Malakas的结构变化特征。结果表明:Malakas变性过程经历了三个阶段:(1)高层扰动加强期,高层的正位涡产生的气旋性环流使低层Malakas中心北部的斜压带西侧产生负的温度平流,表现为冷空气的入侵;(2)Malakas和中纬度系统相互作用时期,台风北上导致斜压带出现,深对流的爆发使低层暖湿气流沿着斜压带上升,快速上升气流中的潜热释放导致低PV空气向对流层上部净输送,在其北部高层重新构建出一个脊;(3)Malakas变性成温带气旋,残存的台风内核与斜压带逐渐合并,负的位涡平流带着非绝热外出流驱动了下游最初脊的构建,加速并且固定了中纬度急流,并整体放大了上层Rossby波模式。     

Application of HF radar currents to oil spill modelling

In this work, the benefits of high-frequency (HF) radar currents for oil spill modeling and trajectory analysis of floating objects are analyzed. The HF radar performance is evaluated by means of comparison between a drifter buoy trajectory and the one simulated using a Lagrangian trajectory model. A methodology to optimize the transport model performance and to calculate the search area of the predicted positions is proposed. This method is applied to data collected during the Galicia HF Radar Experience. This experiment was carried out to explore the capabilities of this technology for operational monitoring along the Spanish coast. Two long-range HF radar stations were installed and operated between November 2005 and February 2006 on the Galician coast. In addition, a drifter buoy was released inside the coverage area of the radar. The HF radar currents, as well as numerical wind data were used to simulate the buoy trajectory using the TESEO oil spill transport model. In order to evaluate the contribution of HF radar currents to trajectory analysis, two simulation alternatives were carried out. In the first one, wind data were used to simulate the motion of the buoy. In the second alternative, surface currents from the HF radar were also taken into account. For each alternative, the model was calibrated by means of the global optimization algorithm SCEM-UA (Shuffled Complex Evolution Metropolis) in order to obtain the probability density function of the model parameters. The buoy trajectory was computed for 24 h intervals using a Monte Carlo approach based on the results provided in the calibration process. A bivariate kernel estimator was applied to determine the 95% confidence areas. The analysis performed showed that simulated trajectories integrating HF radar currents are more accurate than those obtained considering only wind numerical data. After a 24 h period, the error in the final simulated position improves using HF radar currents. Averaging the information from all the simulated daily periods, the mean search and rescue area calculated using HF radar currents, is reduced by approximately a 62% in comparison with the search area calculated without these data. These results show the positive contribution of HF radar currents for trajectory analysis, and demonstrate that these data combined with atmospheric forecast models, are of value for trajectory analysis of oil spills or floating objects.     

长水平段水平井井眼轨道优化设计方法

井眼轨道优化设计是长水平段水平井降低摩阻扭矩的有效途径之一,利用先进的计算机软件对轨道设计关键参数进行优选,可以得到优化轨道设计,从而达到降低施工难度的目的。结合华北油田某井工程实列,论述了长水平段水平井井眼轨道优化设计方法。     

A Cascade Approach for Global Trajectory Tracking Control of Underactuated AUVs

A global trajectory tracking controller is presented for underactuated AUVs with only surge force and yaw moment in the horizontal plane. A transformation is introduced to represent the tracking error system into a cascade form. The global and uniform asymptotic stabilization problem of the resulting cascade system is reduced to the stabilization problem of two subsystems by use of the cascade approach. For the stabilization of the subsystem involving the yaw moment, a control law is proposed based on the feedback linearization method. Another subsystem is stabilized by designing a fuzzy sliding mode controller which can offer a systematical means of constructing a set of shrinking-span and dilating-span membership functions. In order to demonstrate the practicability of the proposed controller, control constraints, parameter uncertainties, and external disturbances are considered according to practical situation of AUVs. Simulation results show very good tracking performance and robustness of the proposed control schemes.     

贵州安顺市PM2.5气象输送条件及贡献源空间分布

利用贵州省安顺市2015—2019年大气污染物资料和气象资料,分析安顺市空气质量特征和主要大气污染物特征,通过TrajStat软件中HYSPLIT模型的后向轨迹模式,结合GDAS气象数据、PM_2.5浓度,分析不同季节输送途径及其污染轨迹,采用潜在源贡献作用和浓度权重轨迹分析方法,分析研究期内所有PM_2.5污染日（PM_2.5日浓度高于75 μg·m^-3）输送轨迹垂直与水平方向分布特征。结果表明: PM_2.5是安顺城区主要大气污染物,冬季输送污染轨迹占比较大,输送方向主要为贵州东北方向、偏南方向; 污染日PM_2.5输送路径以贵州东北方向近距离输送为主,该类轨迹基本分布在880—980 hPa高度; 潜在源高值区主要集中在贵阳整个地区、毕节织金县、黔西市、金沙县等,高贡献值区主要集中在安顺紫云县、镇宁县、毕节织金县、大方县等。