一类混合迭代算法在约束预测控制中的应用

为了改进多变量约束预测控制的滚动优化算法,对路径跟踪法和粒子群算法进行了理论研究,提出了一种将路径跟踪法和粒子群算法相结合的混合迭代算法,并用该混合算法对最具代表性的动态矩阵控制进行了滚动优化.仿真结果表明:对由于参数选择引起矩阵奇异时,路径跟踪法无法求出最优解,而基于混合迭代算法的优化算法可以得到最优解.采用路径跟踪法和粒子群算法相结合的混合迭代算法对多变量约束预测控制进行滚动优化,保证了优化算法的快速性和可行性.     

基于PSO的一类线性系统参数辨识方法研究

研究了一种线性系统的参数精确辨识方法;首先采用PSO(Particle Swarm Optimization,粒子群优化)方法对模型进行优化迭代,并选择合适误差准则作为粒子群优化算法的适应度函数,以迭代每个粒子所对应的参数速度和大小;在此基础上,寻找最小适应度值的粒子,推导出最优的适应度函数值,实现系统参数的实时、精确估计;最后通过实验验证了基于粒子群优化算法的参数辨识法的准确性和有效性。     

基于粒子群优化及高斯过程回归的铅酸电池荷电状态预测

为了提高铅酸电池荷电状态(SOC)的预测准确率,该文提出一种基于粒子群优化的高斯过程回归(PSO-GPR)算法。该算法的核心思想是通过粒子群优化(PSO)算法来解决高斯过程回归(GPR)模型中的超参数优化问题。PSO-GPR首先随机生成一个粒子群,群中的每个粒子包含对应的GPR超参数信息。随后执行如下迭代步骤:根据当前每个粒子的超参数信息训练对应的GPR模型并评估该模型的性能,结合适应度函数和每个模型的评估结果计算出每个粒子的适应度,并更新每个粒子中的超参数信息;经过多次迭代后,找到粒子群中适应度最小的粒子;最后从该粒子中提取相应的超参数信息,并训练最终的GPR预测模型。在铅酸电池数据集上的实验结果表明,所提方法优于对比模型。     

基于Meanshift优化粒子滤波算法的低空平台下车辆跟踪

针对低空平台下运行车辆的特点, 提出一种基于Meanshift粒子优化的粒子滤波算法实现低空平台下的车辆跟踪. 该算法使用颜色表示目标, 通过Meanshift算法对粒子滤波进行迭代优化, 减少了稳健跟踪一个目标所需的粒子数, 提高了算法的运行效率, 在小目标和多目标的情况下也能稳健跟踪. 实验结果表明, 该算法具有较强的鲁棒性和稳定性, 能实现低空平台下目标车辆的快速跟踪.     

基于AEPSO优化的神经网络多步预测控制

为提高神经网络预测控制的性能,提出了基于自适应扩展粒子群优化的神经网络预测控制方案。基本PSO算法中,每个粒子的更新受粒子个体极值和局部极值的影响,为了提高其全局收敛性,采用多粒子策略,使每个粒子的更新受更多其他粒子的影响;为提高收敛速度,采用自适应策略,对参数c0进行自适应调整,使c0随着迭代次数的增加而逐渐减小,这样,在PSO算法的搜索过程中,随着迭代次数的增加,搜索区域会越来越小,从而加快PSO算法收敛速度。运用该算法实现神经网络预测控制中的滚动优化,在有限时域内对控制序列进行寻列,给出基于粒子群优化的神经网络预测控制系统的稳定性证明。仿真结果表明,基于粒子群优化的神经网络预测控制系统具有良好的跟踪性能。     

改进粒子滤波在行人跟踪中的应用

为提高粒子滤波在目标跟踪中的性能,将萤火虫算法(Firefly Algorithm,FA)的优化思想引入粒子滤波,并用自适应差分进化(Self-adaptive Differential Evolution,SaDE)算法代替粒子滤波的重采样,提出一种改进的粒子滤波跟踪算法,并采用新的跟踪特征HSV-iLBP进行跟踪.该算法将FA用于粒子滤波的重要性采样,通过计算迭代来抽取更加有效的粒子,并将粒子滤波的重采样过程看作求解目标函数的最值问题,通过自适应差分进化算法的迭代寻找最优粒子,改善粒子的退化和贫化问题.HSV-iLBP模型由于结合了维数低的HSV颜色特征和iLBP纹理特征,从而在提高跟踪鲁棒性的同时,能有效降低计算复杂度.通过仿真实验,验证了改进算法在行人跟踪上具有更好的精度和速度.     

基于改进粗糙化粒子滤波的磁偶极子跟踪

针对一般非线性滤波方法对磁偶极子跟踪时存在精度不高和滤波发散的问题,提出了一种改进粗糙化粒子滤波算法进行求解.该算法基于欧拉离散化方法,将连续随机滤波方法引入粗糙化粒子滤波框架,计算出在K-L散度意义下的最优控制量,将其作为粗糙化均值,以克服粒子贫化问题.建立了磁偶极子目标跟踪的连续时间状态空间模型,并给出了算法具体实现,通过仿真实验,将该算法与目前采用的磁偶极子目标跟踪算法进行对比,结果表明所提出的算法精度较高,且性能稳定.     

粒子滤波算法在视频目标跟踪中的应用

首先介绍粒子滤波的基本理论,然后构建粒子滤波视频目标跟踪系统的状态模型和观测模型,进而根据状态模型和观测模型提出一种基于粒子滤波的视频目标跟踪算法,并通过实际的视频目标跟踪系统对算法进行实验分析,说明粒子滤波算法在视频目标跟踪中的优越性。     

粒子滤波算法在视频目标跟踪中的应用

首先介绍粒子滤波的基本理论,然后构建粒子滤波视频目标跟踪系统的状态模型和观测模型,进而根据状态模型和观测模型提出一种基于粒子滤波的视频目标跟踪算法,并通过实际的视频目标跟踪系统对算法进行实验分析,说明粒子滤波算法在视频目标跟踪中的优越性.     

基于在线判别分析的鲁棒L1视觉跟踪算法

通过分析经典L1视觉跟踪算法在粒子滤波框架下的采样粒子分布与运动目标真实状态的差异,提出了一种基于在线判别分析的改进L1视觉跟踪算法.该跟踪算法利用基于在线逻辑回归模型的判别分析及其更新过程,自主获取运动目标的实时状态与变化,增强运动目标与背景信息之间的可判别性,以实现采样粒子的自适应重要性筛选.通过筛选,尽量排除与运动目标差异大的粒子,降低这些粒子造成的跟踪不稳定性,并减少L1优化求解的次数,从而提高跟踪的鲁棒性和整个算法的执行效率.与五种跟踪算法在四组公开视频上的实验结果表明:提出的算法能够长时间准确地对运动目标进行跟踪,同时相对经典L1跟踪算法而言,有效地降低了计算复杂度.     

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.     

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.     

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.