Railway Passenger Flow Forecasting by Integrating Passenger Flow Relationship and Spatiotemporal Similarity

Railway passenger flow forecasting can help to develop sensible railway schedules,make full use of railway resources,and meet the travel demand of passengers.The structure of passenger flow in railway networks and the spatiotemporal relationship of passenger flow among stations are two distinctive features of railway passenger flow.Most of the previous studies used only a single feature for prediction and lacked correlations,resulting in suboptimal performance.To address the above-mentioned problem,we proposed the railway passenger flow prediction model called Flow-Similarity Attention Graph Convolutional Network(F-SAGCN).First,we constructed the passenger flow relations graph(RG)based on the Origin-Destination(OD).Second,the Passenger Flow Fluctuation Similarity(PFFS)algorithm is used to measure the similarity of passenger flow between stations,which helps construct the spatiotemporal similarity graph(SG).Then,we determine the weights of the mutual influence of different stations at different times through an attention mechanism and extract spatiotemporal features through graph convolution on the RG and SG.Finally,we fused the spatiotemporal features and the original temporal features of stations for prediction.The comparison experiments on a railway bureau’s accurate railway passenger flow data show that the proposed F-SAGCN method improved the prediction accuracy and reduced the mean absolute percentage error(MAPE)of 46 stations to 7.93%.

IMPROVEMENT TO THE EVAPORATION DUCT MODEL BY INTRODUCING NONLINEAR SIMILARITY FUNCTIONS IN STABLE CONDITIONS

Modified refractivity (M) profile is an important parameter to describe the atmospheric refraction environment,as well as a key factor in uniquely evaluating electromagnetic propagation effects.In order to improve the model-derived M profile in stable (especially very stable) conditions,three nonlinear similarity functions,namely BH91,CB05,SHEBA07,are introduced in this paper to improve the original Babin_V25 model,and the performances of these modified models are verified based on the hydrometeorological observations from tower platforms,which are finally compared with the original Babin_V25 model and Local_HYQ92 model.Results show that introducing nonlinear similarity functions can significantly improve the model-derived M profile;especially,the newly developed SHEBA07 functions manage to reduce the predicted root mean square (rms) differences of M and M slope (for both 0-5m and 5-40m) by 64.5%,16.6%,and 60.4%,respectively in stable conditions.Unfortunately,this improved method reacts little on the evaporation duct height;in contrast,Local_HYQ92 model is capable of reducing the predicted rms differences of M,M slope (for both 0-5m and 5-40m),and evaporation duct height by 76.7%,40.2%,83.7%,and 58.0% respectively.Finally,a new recommendation is made to apply Local_HYQ92 and Babin_SHEBA07 in very stable conditions considering that M slope is more important than evaporation duct height and absolute M value in uniquely determining electromagnetic propagation effects.

Pore-throat structure characteristics and its impact on the porosity and permeability relationship of Carboniferous carbonate reservoirs in eastern edge of Pre-Caspian Basin

Carboniferous carbonate reservoirs at the eastern edge of the Pre-Caspian Basin have undergone complex sedimentation,diagenesis and tectonism processes,and developed various reservoir space types of pores,cavities and fractures with complicated combination patterns which create intricate pore-throats structure.The complex pore-throat structure leads to the complex porosity-permeability relationship,bringing great challenges for classification and evaluation of reservoirs and efficient development.Based on the comprehensive analysis on cores,thin sections,SEM,mercury intrusion,routine core analysis and various tests,this paper systematically investigated the features and main controlling factors of pore-throats structure and its impact on the porosity-permeability relationship of the four reservoir types which were pore-cavity-fracture,pore-cavity,pore-fracture and pore,and three progresses are made.(1)A set of classification and descriptive approach for pore-throat structure of Carboniferous carbonate reservoirs applied to the eastern edge of the Pre-Caspian Basin was established.Four types of pore-throat structures were developed which were wide multimodal mode,wide bimodal mode,centralized unimodal mode and asymmetry bimodal mode,respectively.The discriminant index of pore-throat structure was proposed,realizing the quantitative characterization of pore-throat structure types.(2)The microscopic heterogeneity of pore reservoir was the strongest and four types of pore-throat structures were all developed.The pore-fracture and pore-cavity-fracture reservoirs took the second place,and the microscopic heterogeneity of pore-cavity reservoir was the weakest.It was revealed that the main controlling factor of pore-throat structure was the combination patterns of reservoir space types formed by sedimentation,diagenesis and tectonism.(3)It was revealed that the development of various pore-throat structure types was the important factor affecting poroperm relationship of reservoirs.The calculation accuracy of permeability of reservoirs can be improved remarkably by subdividing the pore-throat structure types.This study deepens the understanding of pore-throat structure of complicated carbonate reservoirs,and is conducive to classification and evaluation,establishment of precise porosity-permeability relationship and highly efficient development of carbonate reservoirs.

Exploring landslide erosion volume-area scaling relationships by slip depth using changes in DTMs for basin sediment volume estimation

Landslides produce large quantities of sediment deposits and reduce reservoir life. This study investigated landslides at the Shihmen Reservoir basin in Taiwan that were induced by Typhoon Sinlaku and Typhoon Jangmi in 2008. We formulate scaling relationships between landslide erosion volume and area and conclude that sediment budget can be estimated based on the easier-todetermine landslide erosion area. The methodologies applied for the investigation were geomorphological analysis through 5 m × 5 m digital terrain models(DTMs) of the basin created before and after the landslide events and spatial analysis through a geographic information system. The erosion area and volume of landslides were measured through the subtraction of DTMs produced before and after the events. Statistical analysis revealed that the landslide erosion frequency–magnitude distribution exhibited power-law behaviors with a scaling exponent of 2.15 for the frequency–area distribution and 1.66 for the frequency–volume distribution. This paper proposes different scaling relationships for different moving depths, and landslide erosion volumes were estimated on the basis of depth; thus, landslides of different scales can be distinguished to avoid errors in volume estimation. Two different scaling exponents are proposed: 1.21 for landslide erosions with depths of less than 2 m and 1.01 for landslide erosions with depths of more than 2 m. The proposed scaling relationships are practical for landslide erosion volume estimation by different depths according to the landslide area, and they can provide preliminary results for sediment budget planning in a reservoir basin.

PMS-Sorting:A New Sorting Algorithm Based on Similarity

Borda sorting algorithm is a kind of improvement algorithm based on weighted position sorting algorithm,it is mainly suitable for the high duplication of search results,for the independent search results,the effect is not very good and the computing method of relative score in Borda sorting algorithm is according to the rule of the linear regressive,but position relationship cannot fully represent the correlation changes.aimed at this drawback,the new sorting algorithm is proposed in this paper,named PMS-Sorting algorithm,firstly the position score of the returned results is standardized processing,and the similarity retrieval word string with the query results is combined into the algorithm,the similarity calculation method is also improved,through the experiment,the improved algorithm is superior to traditional sorting algorithm.

Functional Brain Network Learning Based on Spatial Similarity for Brain Disorders Identification

Functional brain network (FBN) measures based on functional magnetic resonance imaging (fMRI) data, has become important biomarkers for early diagnosis and prediction of clinical outcomes in neurological diseases, such as Alzheimer’s diseases (AD) and its prodromal state (i.e., Mild cognitive impairment, MCI). In the past decades, researchers have developed numbers of approaches for FBN estimation, including Pearson’s correction (PC), sparse representation (SR), and so on. Despite their popularity and wide applications in current studies, most of the approaches for FBN estimation only consider the dependency between the measured blood oxygen level dependent (BOLD) time series, but ignore the spatial relationships between pairs of brain regions. In practice, the strength of functional connection between brain regions will decrease as their distance increases. Inspired by this, we proposed a new approach for FBN estimation based on the assumption that the closer brain regions tend to share stronger relationships or similarities. To verify the effectiveness of the proposed method, we conduct experiments on a public dataset to identify the patients with MCIs from health controls (HCs) using the estimated FBNs. Experimental results demonstrate that the proposed approach yields statistically significant improvement in seven performance metrics over using the baseline methods.

Research on community detection algorithm based on site topic similarity and topology

Considering the deviation in content of community detection resulting from the tow accuracy of resource relevance, an algorithm based on the topology of sites and the similarity between their topics is proposed. With topic content factors fully considered, this algorithm can search for topically similar site clusters on the premise of inter-site topology. The experimental results show that the algorithm can generate a more accurate result of detection in the real network.

A Personalized Cloud Services Recommendation Based on Cooperative Relationship between Services

A personalized recommendation for cloud services, which is based on usage history and the cooperative relationship of cloud services, is presented. According to service groups, a service group could be defined as several services that were used together by one user at a time, and cooperative relationship between each two services can be calculated. In the process of recommendation, the services which are highly related to the service that the user has selected would be obtained firstly, the result should then take the QoS (Quality of Service) similarity between service’s QoS and user’s preference into account, so the final result combining the cooperative relationship and similarity will meet the functional needs of users and also meet the user’s personalized non-functional requirements. The simulation proves that the algorithm works effectively.

Quantitative structure-activity relationship of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives with AT1 receptor antagonistic activity

The quantitative structure-activity relationship(QSAR) of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives was studied.Three different alignment methods were used to get the models of the comparative molecular field analysis(CoMFA),the comparative molecular similarity indices analysis(CoMSIA),and the hologram quantitative structure?activity relationship(HQSAR).The statistical results from the established models show believable predictivity based on the cross-validated value(q2>0.5) and the non-validated value(r2>0.9),The analysis on contour maps of CoMFA and CoMSIA models suggests that hydrophobic and hydrogen-bond acceptor fields are important factors that affect the AT1 antagonistic activity of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives besides the steric and electrostatic fields,The structural modification information from different atom contributions in the HQSAR model is in agreement with that in the 3D-QSAR models.

基于多特征符号聚合近似和层次聚类的户变关系识别方法

针对低压配电台区拓扑档案中可能存在的户变关系异常问题,文中提出了一种基于多特征符号聚合近似(MF-SAX)和层次聚类的户变关系识别方法。首先,运用符号聚合近似表达方法将用户电压时间序列转化为字符串序列,并引入电压波动系数和电压变化趋势两个附加参数对其特征表达进行强化。然后,基于编辑距离生成用户电压曲线相似性矩阵,并结合层次聚类算法实现户变关系的识别。最后,实际算例结果表明,提出的方法相比于现有方法准确率更高,误报更少,能直接应对数据缺失的情况,且具有更高的效率。

向斜构造区特厚煤层开采覆岩结构稳定性及突水压架机理

针对陕西省永陇矿区褶曲构造带突水压架事故频发问题,以陕西省郭家河煤矿为工程背景,采用现场调研、物理实验与理论分析的方法,确定了导致工作面突水压架的主要含水层,得出了向斜构造区煤层开采覆岩破断失稳特征,建立了考虑承压水作用的覆岩结构力学模型,推导了工作面突水压架的临界水压力,揭示了向斜构造区突水压架机理。研究表明:①1303、1304、1308等已开采工作面在向斜轴部区域均发生过突水压架事故,宜君组岩层是导致工作面突水事故的主要含水层,煤层之上102.5 m处厚度为28.53 m的中粒砂岩为隔水关键层。隔水关键层断裂后,其上部100.51 m载荷层同步破断,导水裂隙带导通宜君组含水层。②在向斜构造区俯采阶段,顶板覆岩具有多层亚关键层并形成多离层区。向斜轴部岩层破断角竖直发育,顶板破坏程度最高,压架风险最大。③顶板突水致使覆岩结构失稳是导致压架事故发生的关键。承压水对顶板岩层稳定性的影响主要表现为:增加了覆岩载荷传递的连续性,降低了组合亚关键层的承载能力;构成了组合亚关键层的附加载荷。④防止突水压架所需的支护阻力随承压水压力的增大而加速增加,工作面发生突水压架事故的临界承压水压力为0.98 MPa。控制导水裂隙带发育高度与降低宜君组承压水压力是保证工作面不发生压架事故的关键。

知识关系、知识协奏能力与企业创新绩效

知识关系和知识协奏能力影响着共享知识的利用价值及利用效率,也是提高企业创新绩效的关键。文章结合知识学习过程,将知识关系分为知识相似性和知识互补性,以2010—2022年联合申请过专利的中国深沪A股上市高新技术企业为研究样本,实证检验知识关系对企业创新绩效的影响及知识协奏能力的调节作用。结果表明:知识相似性在知识识别阶段发挥重要作用,对企业创新绩效呈“倒U”型影响;知识互补性主要作用于知识吸收阶段,对企业创新绩效呈正向影响;企业知识协奏能力强化了知识相似性和知识互补性对创新绩效的影响。异质性分析表明,知识相似性更能促进大规模企业的创新绩效,而知识互补性更能促进小规模企业的创新绩效。

医患人格相似性对在线医疗交互效果的影响研究

本研究基于大五人格理论、人际吸引理论和信息质量理论,探索了在线医疗平台中医患人格相似性对交互效果的影响。研究建立了一个包括开放性、责任心、外向性、宜人性和神经质五个人格维度的医患人格相似性与在线交互效果之间的OLS模型和岭回归模型,并进一步考察了医生职称和患者疾病风险的调节作用。实证结果表明,医患人格相似性整体上对交互效果具有正向且显著的影响。具体来说,患者的疾病风险在医患人格相似性与交互效果之间起到正向调节作用,而医生的职称则表现为负向调节作用。在五项人格维度中,开放性、外向性和神经质的相似性对医患交互效果具有积极影响,而责任心和宜人性的相似性则未显示出明显的正向作用。本研究不仅提高了在线医疗互动的理论认识,而且为在线问诊平台的优化及医疗政策制定提供了实证支持。

师—徒深层相似性匹配对合作创新绩效的作用机理

二元关系构成个体层面链接到团队层面的结构洞,具有重要价值和意义,是创新的基本单元。以327对师徒二元关系为研究对象,探索师—徒深层相似性匹配对合作创新绩效的影响机制。结果发现:师—徒深层相似性匹配与合作创新绩效之间呈正相关关系;二元关系紧密度在师—徒深层相似性匹配与合作创新绩效的关系中发挥中介作用;共享心智模式在师—徒深层相似性匹配与合作创新绩效的关系中发挥中介作用;二元关系紧密度和共享心智模式在师—徒深层相似性匹配与合作创新绩效的关系中发挥链式中介作用;导师知识共享行为通过调节师—徒相似性匹配与二元关系紧密度的关系,进而调节二元关系紧密度、共享心智模式在师—徒相似性匹配与合作创新绩效关系中的链式中介作用。

一种基于非独立同分布下K-means算法的系统日志分析方法

系统日志作为记录系统操作和事件信息的重要资源,对保障系统安全和优化系统性能具有至关重要的作用。利用K-means算法进行系统日志分析能够帮助管理员对日志进行分类管理,通过对相似日志条目的自动聚类,提高日志检索和管理的效率。传统K-means聚类算法一般采用欧氏距离作为相似性度量方法,该方法忽略了对象属性之间存在的耦合关系,是假设数据具有独立同分布的特性的,然而在现实的数据中,对象属性之间会存在一些复杂的耦合关系,是非独立同分布的。文章提出一种基于非独立同分布下K-means算法的系统日志分析方法,以非独立同分布的思想进行相似性度量。实验结果表明该方法能够获得较高的准确率和较低的聚类执行时间。

基于混淆矩阵和Fisher准则构造层次化分类器

构造层次化分类器的首要环节是确定各个子分类器的层属关系及其内部组成.从模式间的相似关系入手,实现了一种自动产生层次化分类器结构的方法.为了描述模式间的相似关系,首先提出利用混淆矩阵度量相似性的思路与方法,避免了现有常用度量方法计算量大、假设条件难以成立的不足.进而遵循Fisher准则,设计并实现了模式相似关系分析机(patterns’similarityrelationshipanalyzingmachine,简称PSRAM),将有师指派和无师自组两种常用的模式重组方法有机结合起来,自适应地产生层次化分类器结构.大量测试证实,该方法有效、实用,可以显著地提高分类器的识别性能和稳健性.

多尺度地理空间点群目标相似关系的计算研究

研究多尺度地理空间点群目标相似关系的计算问题。基于4类点群信息,将点群目标包含的信息重新分成统计信息、专题信息、拓扑信息、几何信息和度量信息,这5类信息是影响点群相似性程度的主要因子。根据这5类信息描述参数的特点,给出了各个因子的相似度计算公式,建立了多尺度地理空间点群目标相似关系的计算模型,并通过算例验证了该模型的可行性与有效性,为地图综合质量的评价提供了一种新方法。

面向关联数据的联合式实体识别方法

文中提出一种基于图的、迭代的联合式实体识别方法.初始时,将多类型的、关联的实体数据对象集合构建实体数据对象关系图,将基于语义路径的相似度和属性相似度结合起来判断数据对象是否匹配;然后,合并匹配成功的数据对象,并对对象图中的相应数据对象结点及其周边执行局部图收缩,这两个操作使对象图的局部语义变得更丰富,促使该局部范围内产生出新的候选匹配对象对,以待后续识别,实现相似度传递,形成一个迭代的识别过程.随着不断迭代,对象图的语义不断丰富,提高了联合式实体识别的准确性.通过实验证明文中提出的方法比已有的联合式实体识别方法和基于对象关系的单类型实体识别方法具有更高的准确性.

木瓜属优良品种亲缘关系的AFLP分析

用AFLP技术对29个木瓜属品种的亲缘关系进行分析。用8对引物(EcoRⅠ+3/MseⅠ+3)对基因组DNA进行选择性扩增,共获得1095条扩增带,其中1035条具有多态性,多态带百分率达94.52%,揭示木瓜品种具有丰富的遗传多样性。采用NTSYS-PC软件的DICE法计算样本间的相似系数,UPGMA法进行聚类分析。结果表明:品种间的相似系数在0.4650～0.8339之间,具有相似形态特征的品种优先相聚,29个品种可以划分为4类,且基本对应着贴梗海棠、日本木瓜、木瓜海棠和傲大贴梗海棠,但品种‘猩红与金黄’宜归入贴梗海棠内,而‘碧雪’的分类地位值得进一步探讨。说明AFLP标记技术能较好地揭示木瓜属种质资源的亲缘关系及演化规律。

基于模糊聚类分析的无功电压控制分区

无功电压控制研究中的系统分区是一个非线性的大规模组合优化问题,使用常规方法常难以得到理想的结果。运用模糊聚类分析法将系统分区,并基于电压幅值对无功功率的灵敏度定义了电力系统各节点间的电气距离,对待分类对象的全体作适当的标定,运用传递闭包法求出动态分类,通过计算统计量F最后得出最优分类。该方法所占内存小,计算速度快。经IEEE39节点测试系统对该方法进行了验证,其结果表明:该方法有效、可行。