能源生产的模糊预测

基于经济变量和状态的模糊性,建立计量经济模型,运用模糊聚类(FCM)算法对样本空间进行聚类划分,获取模糊相似矩阵,优化经济变量输入输出关系,对经济变量进行拟合和预测.将模糊聚类方法用于复杂的能源系统,对我国能源生产进行预测,把预测结果与实际值进行了比较,结果表明误差较小,同时还将此预测与多元回归预测进行比较,结果表明用模糊方法对能源生产进行预测效果更好.用同样的方法可以对经济领域中诸如消费、货币需求、产品需求等进行预测,其应用领域是广泛的.     

基于空间相关的逻辑回归模型的城市扩展模拟

建立一种基于空间的逻辑回归模型用于分析和预测城市扩展,这种模型利用空间滤波对因子进行空间平滑得出"隐含变量",从而把原始变量变换为没有空间相关的新变量.利用该模型对新堡市的土地利用变化进行了分析和预测.实验结果表明,新方法比普通逻辑回归模型的预测精度有较大提高,曲线下面积从0.74提高到0.84.     

基于多变量相重构的混沌时间序列预测

提出了一种基于多变量相重构的混沌时间序列预测方法.该预测方法从非线性动力学系统中获取与待预测时间序列相关的信息组成多变量时间序列,首先进行多变量相空间重构,然后利用局域多元线性回归模型在相空间中进行预测,最后从预测出的高维相点中分离出时间序列的预测值.由于考虑了动力学系统中多个变量之间相互耦合的关系,从而增加了重构相空间的系统信息量,使得相空间的相点轨迹更加逼近原系统的动力学行为.与采用单变量进行预测的方法相比,基于多变量相重构的预测方法无论是单步预测还是多步预测,都能有效地提高预测精度,且具有嵌入维数的选择对预测精度影响较小的优点.通过对Lorenz混沌信号进行预测,实验结果验证了方法的有效性.     

基于Logistic算法的考研成绩变量预测方法

针对传统考研成绩变量预测方法的变量关联性低,导致预测结果存在较大误差的问题,提出基于Logistic算法的考研成绩变量预测方法.收集并处理历年考研成绩数据和学生成绩数据,作为成绩变量预测的初始数据.设置考研成绩的预测变量,建立Logistic回归分类算法模型,通过该模型的运算提高考研成绩变量之间的关联性.综合历年考研成绩数据的发展规律以及变量的影响因素分析结果,得出考研成绩变量的预测结果.通过对比实验分析得出结论:基于Logistic算法的考研成绩变量预测方法的预测误差率较低,预测准确性较高.     

我国物价水平影响因素的实证分析

居民消费价格指数是国民经济发展中的重要宏观监控指标之一,由定性分析预测得出可能影响居民消费价格指数的解释变量,选取我国1996年以来的有关数据,通过EVIEWS软件进行对各变量进行计量分析,建立数学模型分析得出货币供应量、国内生产总值和物价水平有较强的正相关关系,并在此基础上提出建议分析.     

中国民用汽车拥有量多层面分析

文章对中国民用汽车拥有量及相关经济变量1985—2015年的年度数据进行了多层面分析.建立单变量Logistic时序模型,对未来民用汽车拥有量进行预测;建立双变量弹性分析模型,研究单个经济变量每变动1%对民用汽车拥有量的影响程度;建立多元线性回归模型,发现人口总数、工业增加值、钢材产量和全国居民消费水平与民用汽车拥有量之间的线性关系.     

我国宏观经济物价模型与"九五"物价走势分析

通过分析与我国宏观经济物价变动密切相关的主要经济变量以及变量以及变量与物价之间的关系,建立我国宏观经济物价模型,得出“高增长、低通胀”的结论,并在此基础上对我国未来的物价水平,走势出大胆预测,对指导我国经济稳定、健康、持续的发展具有现实意义。     

操作变量与前馈变量转换对模型预测控制可行域影响机制

模型预测控制因其解耦性和强鲁棒性得以在过程控制中广泛使用.在实际生产过程中,因操作需要常常放开控制器对部分操作变量的控制,此部分操作变量则转化为前馈变量.变量之间的转换将使系统的结构在方系统、胖系统和瘦系统之间发生转换.对于瘦系统,操作变量的维数少于被控变量,其控制效果往往低于其他结构的系统.同时,原操作变量不被控制器控制后,转换为前馈变量,也会影响对系统的控制效果.可行域能直接反映系统控制效果.在对状态空间模型进行多步预测推导的基础上,将部分控制变量与前馈变量进行转换,用空间几何映射表示变量转换,并分析转换对系统可行域的影响.最后,针对实际生产过程中放开部分控制变量的情况,提出预判机制,以保证系统可控.     

基于BLS-Lasso组合模型的火电厂蒸汽量预测

在火力发电过程中,蒸汽量的准确测量,对于汽轮机机组的经济稳定运行具有重要的意义。针对传统蒸汽量测量方法精度低的问题,提出了一种基于宽度学习系统(broad learning system, BLS)和Lasso (least absolute shrinkage and selection operator)回归模型的组合预测模型。首先利用One-class SVM (one-class support vector machines)算法对样本进行异常值检测,将检测得到的异常值剔除。然后,采用最大信息系数(maximal informationcoefficient, MIC)对特征变量和蒸汽量进行非线性关联性分析,确定宽度学习系统和Lasso回归模型的输入变量,通过训练得出各自的预测结果。最后,通过最优加权组合法确定两单一模型的权重系数,将它们所得的预测结果线性组合,得到最终的预测结果。实例表明,所建立的组合模型有效地缓解了单一模型在变化剧烈的峰值和谷值预测偏差大的问题,能够准确地预测蒸汽量。     

芳烃抽提装置水系统先进控制系统控制技术研究

针对芳烃抽提装置水系统具有多变量、时变、非线性、强耦合、干扰因素多等特点,对水系统控制策略进行了研究,提出了专家控制、多变量预测控制综合使用技术,采用专家控制、多变量预测控制技术建立了水系统生产过程先进控制系统,使水系统先进控制投运取得成功应用.     

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…     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display the geometric objects users concern about swiftly onto the display window. This process includes two operations:retrieve data from database and then draw them onto screen. Accordingly, to improve the efficiency, we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree, the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper introduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets: One is that every node and geometric object in the generalization is assigned with a importance value which denote the importance of them, and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks, and vertexes are total ordered by their importance value. With the help of the generalized R-tree, one can easily retrieve data at different detail levels.Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

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.