空间视角下生产性服务业集聚对城市土地集约利用的影响研究

研究目的:从空间视角研究生产性服务业集聚对中国城市土地集约利用的决定作用,为新型城镇化建设进程中合理安排城市产业布局、促进土地利用方式转变、实现城市经济和土地集约利用协同发展提供新思路。研究方法:空间计量分析法。研究结果:中国城市间生产性服务业集聚和土地集约利用在地理分布上具有显著空间关联性;全国层面,生产性服务业通过专业化集聚、多样化集聚产生的技术外溢效应和集聚规模产生的规模经济效应显著提高了城市土地集约利用水平;分板块层面,生产性服务业多样化集聚和集聚规模对城市土地集约利用的正向效应呈现东、中、东北、西部板块依次递减现象,而专业化集聚对城市土地集约利用的技术外溢效应在西部地区更明显。研究结论:提升生产性服务业集聚水平、促进产业结构优化和人口集聚有利于中国城市集约利用土地资源。     

北京东郊地下水化学成分及演化研究

运用R型聚类分析法和Piper三线图对2014年北京东郊地区地下水水质进行评价,分析该地区水文地球化学类型特征。通过R型聚类,将18种检测指标分为4类。其中,第Ⅰ类中TDS,总硬度,Ca~(2+),Mg~(2+),HCO~-_3,Cl~-以及电导率等对该地区水化学特征的影响最大;第Ⅱ类中既包含影响地下水色度的Fe和Mn,又包含存在线性关系的NH_3-N和COD_(Mn);第Ⅲ类、第Ⅳ类为pH值和NO~-_2,对水质的影响较弱。Piper三线图分析结果表明研究区内地下水沿流向发生水质点位移现象,地下水类型逐渐由Ca-Mg-HCO_3和Ca-Mg-HCO_3-SO_4为主,变为Ca-Mg-Na-HCO_3及Ca-Mg-Na-SO_4-Cl,水质情况发生恶化。但整体水质情况仍良好。R型聚类分析方法与Piper三线图的有效结合,为地下水水质分析提供了科学依据。     

集装箱铁海联运需求及内陆港布局研究

集装箱铁海联运具有运能大、成本低、环保等特点,是节能减排、实现"双碳"目标的关键一环,也是我国多式联运发展的薄弱环节。深度挖掘区域铁海联运潜在货源,合理布局铁海联运重要载体——内陆港,是新时期加快实施运输结构调整,持续落实"公转铁"政策的重要支撑。在剖析我国集装箱铁海联运需求形成机理的基础上,运用聚类分析、SLP等方法,提出内陆港宏观、微观布局整体解决方案,助力我国集装箱铁海联运快速发展。     

一种TDMA信号用户盲分离方法

时分多址（Time Division Multiple Access，TDMA）信号用户分离作为TDMA信号第三方侦收的重要环节，是后续用户内涵信息解译组报、目标测向定位的前提条件。在未知网台规格情况下，无法通过解译用户ID或网控信令的方式对多用户进行分离。基于TDMA信号物理层特征，提出了一种基于DBSCAN（Ddensity-based Spatial Clustering of Applications with Noise）聚类算法的TDMA信号用户盲分离方法。通过对TDMA信号的时频域特征进行提取和聚类，实现对多用户突发时隙进行分离，并利用仿真数据和实际网台数据进行了算法验证。该算法具有良好的抗噪声性能和较高的正确分选率。     

Supply chain planning of vaccine and pharmaceutical clusters under uncertainty: The case of COVID-19

As an abrupt epidemic occurs, healthcare systems are shocked by the surge in the number of susceptible patients' demands, and decision-makers mostly rely on their frame of reference for urgent decision-making. Many reports have declared the COVID-19 impediments to trading and global economic growth. This study aims to provide a mathematical model to support pharmaceutical supply chain planning during the COVID-19 epidemic. Additionally, it aims to offer new insights into hospital supply chain problems by unifying cold and non-cold chains and considering a wide range of pharmaceuticals and vaccines. This approach is unprecedented and includes an analysis of various pharmaceutical features such as temperature, shelf life, priority, and clustering. To propose a model for planning the pharmaceutical supply chains, a mixed-integer linear programming (MILP) model is used for a four-echelon supply chain design. This model aims to minimize the costs involved in the pharmaceutical supply chain by maintaining an acceptable service level. Also, this paper considers uncertainty as an intrinsic part of the problem and addresses it through the wait-and-see method. Furthermore, an unexplored unsupervised learning method in the realm of supply chain planning has been used to cluster the pharmaceuticals and the vaccines and its merits and drawbacks are proposed. A case of Tehran hospitals with real data has been used to show the model's capabilities, as well. Based on the obtained results, the proposed approach is able to reach the optimum service level in the COVID conditions while maintaining a reduced cost. The experiment illustrates that the hospitals' adjacency and emergency orders alleviated the service level significantly. The proposed MILP model has proven to be efficient in providing a practical intuition for decision-makers. The clustering technique reduced the size of the problem and the time required to solve the model considerably.     

企业集群的效率损失及对策

作为一种重要的企业制度,企业集群是值得人们注意的。因为它拥有众多优点。然而我们也应发觉并正视其本身固有的缺点。本文先就企业集群作简要介绍,然后就企业集群的竞争力缺失、拖垮整个区域经济、未必有效降低组织成本、伯川德竞争等问题作一一阐述。最后在此基础上提出若干建议以改进企业集群网络组织。     

基于门架数据的高速公路拥堵识别研究

有效识别高速公路拥堵情况，能为高速公路的交通管控及建设规划提供有效依据。基于高速公路门架数据，提出了一套基于行程时间阈值的拥堵识别分析方法，提取车辆的行程时间集合，利用聚类算法对路段的不同拥堵等级的行程时间阈值进行标定，从而对高速公路拥堵情况进行判别。在实例分析中，以广州市高速公路网为研究对象，开展了拥堵识别分析。结果表明，广州市高速公路总体运行状态良好，80%的时段路段处于顺畅状态。     

基于投影寻踪分类法的苏北地区水足迹及用水效率评价

以2013年苏北地区水资源相关数据为样本,根据水足迹理论构建研究水资源利用效率的综合评价体系,并利用投影寻踪分类法作为研究的主要方法对该体系进行实证分析。结果表明,盐城市用水效率较高,而徐州和宿迁用水效率较低。     

How did COVID-19 change what people buy: Evidence from a supermarket chain

This research takes a retrospective view of the COVID-19 pandemic and attempts to accurately measure its impact on sales of different product categories in grocery retail. In total 150 product categories were analyzed using the data of a major supermarket chain in the Netherlands. We propose to measure the pandemic impact by excess sales – the difference of actual and expected sales. We show that the pandemic impact is twofold: (1) There was a large but brief growth at 30.6% in excess sales associated with panic buying across most product categories within a two-week period; and (2) People spending most of their time at home due to imposed restrictions resulted in an estimated 5.4% increase in total sales lasting as long as the restrictions were active. The pandemic impact on different product categories varies in magnitudes and timing. Using time series clustering, we identified eight clusters of categories with similar pandemic impacts. Using clustering results, we project that product categories used for cooking, baking or meal preparation in general will have elevated sales even after the pandemic.     

基于情感分析和机器学习的用户评论信息挖掘

用户评论文本中的主观情感色彩表达了评价者对产品信息的反馈，对其进行有效挖掘意义重大。针对当前用户评论文本信息未能被充分利用的现状，以Vivo手机用户评论数据为研究对象，构建较完备的手机领域情感词典，对用户评论进行情感倾向分析，得到27 223条评论的手机好评度为91.56%，高于HowNet（情感词典）和NTSUSD（情感极性词典）85.96%的好评度。基于情感分析的结果，采用K-means算法发现对产品具有相似兴趣特征的用户群体，并采用TextRank算法挖掘用户群体的兴趣特征。最后利用SVM（支持向量机）、决策树、随机森林、K-近邻算法4种机器学习方法建立用户分类预测模型。随机森林模型预测准确率可达99.83%。基于情感分析的结果定位用户群体的方法，为企业有针对性地进行不同客户群体的营销和服务工作提供了新的方向。