地铁车站监测与数据预测分析

安全监测在地铁建设和运营中占据着举足轻重的作用,如何建立科学完备的地铁安全监测方案和针对监测数据进行有效合理的分析是当前研究的重点之一.基于合肥市某地铁车站建设工程,主要介绍了该地铁车站工程的监测方案,并采用灰色系统理论建立GM(1,1)沉降数据预测模型.结果显示,该模型取得了良好的拟合和预测效果,为地铁监测数据分析提供有效的方法.     

基于Bi-LSTM网络的广珠城际短期客流预测方法

为提高城际铁路车站短时客流量预测的准确性,本文设计了一种基于双向长短期记忆网络(Bi-LSTM)的预测模型.首先分析了广珠城际铁路车站日客流量的时间分布规律,发现各车站日客流量存在着相似的分布特征,但工作日、周末和节假日客流量呈现出较大差异.以广州南站、珠海站以及小榄站3个车站的进站客流为例,选择时间窗步长为2和4分别...     

基于聚类及优化集成神经网络的地铁车站空调负荷预测

分别从优化算法集成神经网络及将数据聚类后按类建模两方面建立3种模型对地铁车站空调负荷进行逐时预测,结果表明：同一物理量对地铁车站空调负荷所产生的影响程度随时间呈现某种动态变化特征,根据历史数据定量分析这些特征,对精准筛选模型输入参数、提高模型预测精度大有裨益。在3种模型中,粒子群优化算法-神经网络（PSO-BPNN）和果蝇优化算法-神经网络（FOA-BPNN）预测的平均相对误差（MAPE）较单纯神经网络（BPNN）分别降低25.87%和40.08%,聚类-神经网络（Kmeans-BPNN）预测的MAPE比PSO-BPNN及FOA-BPNN分别降低61.12%和51.90%。说明在同等情况下,优化算法集成模型比单纯BPNN预测精度更高,而当区分实际负荷变化特点后,采用聚类后建模比优化集成建模效果更佳。     

改进的季节性指数平滑法预测空调负荷分析

根据空调日总负荷和日平均气温之间的较强相关性,对经典的季节性指数平滑法预测模型中的水平因子项进行修正,并去掉趋势因子项,得到了改进的季节性指数平滑预测模型.以上海某医学中心空调系统作为该空调负荷预测模型的应用实例,在整个预测期内模型平均预测误差为8.8%.这表明改进的季节性指数平滑法适合于办公类建筑空调负荷的预测.     

基于深度学习的地铁短时客流量预测

为了对地铁短时客流流量进行准确预测,建立了一种基于深度学习的地铁短时客流预测方法。通过分析地铁的客流数据,发现周一至周四、周五以及周末的发展模式存在一定的差异。依据该发现,基于深度学习的理论框架,建立了双向长短期记忆网络的地铁短时客流量预测模型。最后以广州体育西路地铁站数据为例进行预测分析,并将预测结果与决策树模型、支持向量机算法以及长短期记忆网络的预测结果进行对比分析。结果表明,双向长短期记忆网络全面优于其他预测算法,且该算法的平均预测精度超过90%,对地铁运力的合理配置等有一定的应用价值。     

基于相空间重构-SVM的公交客流量预测研究

提出了一种基于相空间重构与支持向量机预测公交客流量的新方法.应用互信息法计算公交客流量时间序列的最优时间延迟;应用Ca0氏方法计算其最佳嵌入维数;然后计算出最大Lyapunov指数,证实客流节存在混沌现象.建立相空间重构-支持向量机预测模型并确定训练样本对,对公交客流量数据进行预测.实例证明,该方法能有效地进行客流量预测.     

基于K均值小波神经网络的二阶段空调负荷预测

结合聚类分析和小波神经网络模型,提出一种二阶段空调负荷建模方法,以提高空调负荷预测精度.首先利用K均值聚类算法将原始负荷样本数据依据其统计分布特性划分为若干簇类,以降低数据相关性对建模精度的影响;然后基于对每个划分簇类所属的样本数据建立相应小波神经网络空调负荷预测模型.最后基于De ST平台模拟数据,将构造的小波神经网络预测模型运用于福建某办公大楼的逐时空调负荷预测.通过对比均方根误差(RMSE)和平均绝对误差(MAPE),结果表明该模型的预测精度明显优于传统单一的小波神经网络和BP神经网络模型.     

蝙蝠算法优化极限学习机的电力负荷预测模型

为提高电力负荷预测的准确性,提出蝙蝠算法优化极限学习的电力负荷预测模型.首先收集电力负荷历史数据,然后采用蝙蝠算法对延迟时间和嵌入维以及极限学习的隐含层结点数目进行优化,利用电力负荷历史数据进行重构,最后采用最优隐含层结点数目的极限学习机建立电力负荷预测模型,并采用具体数据仿真测试.实验结果表明:模型建立了整体性能优异的电力负荷预测模型,提高了电力负荷的预测精度.     

基于过程神经网络的短期负荷预测

针对目前常用方法在解决负荷预测问题时,结果往往难以达到工程要求精度的现状,利用过程神经网络输入为时间函数以及预测精度高的特点,建立了基于过程神经网络的电力系统短期负荷预测模型;给出了模型的结构,基于函数正交基展开的离散数据拟合方法以及模型的学习算法.针对东北某地区电网的日负荷数据,进行了模型训练和负荷预测正确性的研究.结果表明,所建立的预测模型对负荷的预测准确率高,优于BP神经网络负荷预测模型的预测结果.     

屏蔽门模式环境控制的特性及经济分析

介绍地铁环境控制的3种模式,分析屏蔽门模式环境控制的特性及负荷模拟计算,对3种地铁环境控制模式进行经济分析比较,结果表明,屏蔽门模式是一种最经济的地铁环境控制模式.屏蔽门隔离隧道内热空气与车站内空调冷气之间的交换,使车站成为一个独立的空调场所,可以显著降低车站空调的运行能耗,为乘客提供一个舒适、安全的候车环境.一个典型车站的国产化屏蔽门系统投资费用在1000万元左右,可节省470万元的车站土建及制冷空调设备投资,且每年可节省电2×106kW·h以上,预计5年内就可收回成本.     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

海南岛地体及其毗邻陆缘晚中生代—新生代古地磁研究和构造演化

本文叙述了对海南岛及其毗邻大陆边缘白垩纪到第四纪地层岩石进行古地磁研究的全部工作过程。通过分析岩石中剩余磁矢量的磁偏角及磁倾角的变化,提出海南岛白垩纪以来经历的构造演化模式如下:早期伴随顺时针旋转而向南迁移,后期伴随逆时针转动并向北运移。联系该地区及邻区的地质、地球物理资料,对海南岛上述的构造地体运动提出以下认识:北部湾内早期有一拉张作用,主要是该作用使湾内地壳显著伸长减薄,形成北部湾盆地。从而导致了海南岛的早期构造运动,而海南岛后期的构造运动则主要是受南海海底扩张的影响。海南地体运动规律的阐明对于了解北部湾油气盆地的形成演化有重要的理论和实际意义。     

Exciton Seebeck in Molecular Systems

Various applications relevant to the exciton dynamics,such as the organic solar cell,the large-area organic light-emitting diodes and the thermoelectricity,are operating under temperature gradient.The potential abnormal behavior of the exicton dynamics driven by the temperature difference may affect the efficiency and performance of the corresponding devices.In the above situations,the exciton dynamics under temperature difference is mixed with     

Achieving Unusual States of Matter Under High Pressure

The elongation method,originally proposed by Imamura was further developed for many years in our group.As a method towards O(N)with high efficiency and high accuracy for any dimensional systems.This treatment designed for one-dimensional(ID)polymers is now available for three-dimensional(3D)systems,but geometry optimization is now possible only for 1D-systems.As an approach toward post-Hartree-Fock,it was also extended to     

《Chinese Science Bulletin》SUBJECT INDEX TO VOLUME 59(2014)

正~~     

An on-line scaling method for improving scalability of a database cluster

The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on-line scaling without interrupting service. To support more client's queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on-line scaling method. Our method improves the existing on-line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e. , we decrease the number of data copy by reusing the backup data. Also, our on-line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time.     

An improved R-tree based on childnode''s probability

R-Tree is a good structure for spatial searching. But in this indexing structure,either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).     

Integrating GIS Web services based on mediating architecture

The geographic information service is enabled by the advancements in general Web service technology and the focused efforts of the OGC in defining XML-based Web GIS service. Based on these models, this paper addresses the issue of services chaining,the process of combining or pipelining results from several interoperable GIS Web Services to create a customized solution. This paper presents a mediated chaining architecture in which a specific service takes responsibility for performing the process that describes a service chain. We designed the Spatial Information Process Language (SIPL) for dynamic modeling and describing the service chain, also a prototype of the Spatial Information Process Execution Engine (SIPEE) is implemented for executing processes written in SIPL. Discussion of measures to improve the functionality and performance of such system will be included.     

Tracking data management using topology of moving object database system for moving object constrained trajectory in LBS application

Advances in wireless technologies and positioning technologies and spread of wireless devices, an interest in LBS (Location Based Service) is arising. To provide location based service, tracking data should have been stored in moving object database management system (called MODBMS) with proper policies and managed efficiently. So the methods which acquire the location information at regular time intervals then, store and manage have been studied. In this paper, we suggest tracking data management techniques using topology that is corresponding to the moving path of moving object. In our techniques, we update the MODBMS when moving object arrived at a street intersection or a curved road which is represented as the node in topology and predict the location at past and future with attribute of topology and linear function. In this technique, location data that are corresponding to the node in topology are stored, thus reduce the number of update and amount of data. Also in case predicting the location,because topology are used as well as existing location information, accuracy for prediction is increased than applying linear function or spline function.