应用支持向量机的空中交通流量组合预测模型

为了提高空中交通流量预测的准确性,研究了将支持向量机(support vector machine, SVM)应用于空中交通流量预测的方法,建立了基于SVM的自回归预测模型,讨论了模型参数确定等关键问题.在SVM预测模型基础上,将SVM与多项式和鲁棒自回归预测模型结合,提出组合预测模型.利用北京周边空域实测流量数据进行的对比实验结果表明: SVM预测模型的预测误差小于5%, 组合预测模型的预测误差小于2%, 均优于多项式和鲁棒自回归预测模型;组合预测模型的预测精度和稳定性整体上又优于SVM预测模型.     

快速路交通事件持续时间预测模型研究

针对城市快速路交通事件持续时间影响因素的复杂性和不确定性,结合贝叶斯网络和非参数回归方法,提出了一种新的快速路交通事件持续时间预测模型.采用上海市快速路监控中心数据,经过降噪处理,生成样本数据;在分析样本数据特征基础上,确定了贝叶斯网络的结构学习方法与参数学习方法;对贝叶斯网络模型的结果用非参数回归算法生成持续时间预测值.最后,对模型预测精度进行了验证,发现模型预测效果较好.     

基于改进型贝叶斯组合模型的短时交通流量预测

针对短时交通流量预测的难题,在传统贝叶斯组合模型进行改善的基础上,提出一种改进型贝叶斯组合模型.该模型只根据各基本预测模型当前时刻之前几个交通流量的预测表现,通过提出的分配算法实时更新组合模型中各个基本预测模型的权重,从而改善了传统贝叶斯组合模型权重计算迭代步长过长的缺陷,提高了贝叶斯组合模型对各个基本预测模型预测精度的灵敏性.通过对实地的交通流量的预测发现,基于改进型贝叶斯组合模型的预测精度不仅优于单一的预测方法,而且也优于传统的贝叶斯组合模型,从而证明了改进型贝叶斯组合模型有效提高预测的可靠性和具有一定的实用性.     

基于非负矩阵分解的OD矩阵预测

提出了一种非负矩阵分解-自回归模型,并用该模型对居民出行流量进行预测.该模型首先利用非负矩阵分解方法挖掘城市区域内的居民出行特征,而后在非负矩阵分解获得的特征矩阵和系数矩阵基础上对时序系数矩阵建立自回归模型,进而对起讫矩阵进行预测.以北京市出租车数据为基础,与时空权重K近邻、传统K近邻、反向神经网络、朴素贝叶斯、随机森林和C4.5决策树回归模型对比,实验结果表明,该模型的预测准确率有显著提升.     

投影寻踪自回归模型在长江径流量预测中的应用

为准确预测长江径流量,引入投影寻踪自回归模型,用自相关分析技术确定预测因子,构造了新的投影指标函数,并用基于实数编码的加速遗传算法优化投影指标函数,建立了投影寻踪自回归流量预测模型.将该模型应用于长江径流量的预测,结果表明用该模型预测长江流量时序是可行和有效的.     

贝叶斯预测模型在气温变化预测中的应用

贝叶斯预测模型是运用贝叶斯统计方法进行的一种预测,贝叶斯统计不同于一般统计方法,其不仅利用模型信息和数据信息,而且充分利用了样品的先验信息.根据贝叶斯预测模型的特点,介绍了几个贝叶斯预测模型的预测过程和计算步骤,并对南宁地区自1970年以来19年间的气温变化进行了预测.根据计算结果,分析了不同贝叶斯预测模型的预测特点,并给出了几点结论.     

贝叶斯预测模型在矿物含量预测中的应用

矿物含量预测是资源评价中经常遇到的问题,贝叶斯预测模型是运用贝叶斯统计方法进行的一种预测.贝叶斯统计不同于一般的统计方法,其不仅利用模型信息和数据信息,而且充分利用先验信息.根据贝叶斯预测模型的特点,介绍了几个贝叶斯观测模型的预测过程和计算步骤,并对白鹿塬水家嘴剖面的mg2+含量进行了观测,根据计算结果,分析了不同贝叶斯预测模型的预测特点,并给出了几点结论.     

基于贝叶斯优化高斯过程回归法的再生混凝土力学性能预测

为了更准确地预测再生骨料混凝土的抗压强度与弹性模量,建立了一个比以往研究大的数据库,具有730组数据,为建立可靠的预测模型奠定了基础。提出了贝叶斯优化的高斯过程回归方法,选取再生粗骨料体积分数、水灰比、混合粗骨料吸水率、细骨料与总骨料比、粗骨料与水泥比、混合粗骨料饱和表面干密度等6个参数作为影响因素,同时建立了再生骨料混凝土抗压强度和弹性模量预测模型。通过比较抗压强度、弹性模量的预测值与实验值,发现二者较为接近,说明该方法具有一定的可靠性。将贝叶斯优化的高斯过程回归与高斯过程回归、支持向量机回归、随机森林回归、人工神经网络进行比较,并选取4个统计指标对模型进行评价,结果表明贝叶斯优化的高斯过程回归预测抗压强度和弹性模量精度较高,相关系数分别达到了0.91和0.93。这说明贝叶斯优化的高斯过程回归方法对预测再生骨料混凝土的抗压强度和弹性模量同时适用。     

混凝土碳化深度的贝叶斯自回归预测分析

总结和分析了影响混凝土碳化的主要因素及碳化深度计算模型,讨论了参数随机性及不确定性对碳化深度预测计算结果的影响.根据贝叶斯分析的基本原理,研究了混凝土碳化深度预测的贝叶斯自回归方法.该方法根据马尔可夫链(Markov Chain)的概率密度演化,利用吉布斯(Gibbs)抽样及蒙特卡洛(Monte Carlo)数值模拟,建立了混凝土碳化深度的随时贝叶斯自回归模型.该模型形式简单,收敛性好,且具有较高的预测精度.利用该方法和实测的碳化深度结果,建立自回归模型,可以对混凝土碳化深度进行更新预测.     

基于贝叶斯超出表现模型的城市需水量组合预测

运用营口市人均综合用水量的历史数据,分别采用多元线性回归模型和BP神经网络模型对该市人均综合用水量进行预测,最后建立贝叶斯超出表现模型对所得到的单项预测值进行组合,实证分析结果表明,该组合预测模型获得了更为精确的预测效果,可以作为城市人均综合用水量预测的有效工具.     

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)

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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.