基于神经网络的多传感加权融合算法的研究

数据融合技术是无线传感器网络的一个关键的技术,能减少传感器的传输量,从而明显提高网络的感知性能,延长网络生命周期,减少时间延迟.多传感器的数据融合可以获得比单一传感器更多,更准确的信息.针对从含有噪声的测量数据中估计出监测变量,对自适应加权融合算法进行改进,基于信任度方法对测量数据进行数据预处理,然后基于神经网络误差修正的方法实现各传感器权重的自适应匹配,从而得到较为准确的估计值.通过对比仿真实验,本文算法的融合结果在精度、容错性方面均优于均值估计算法和自适应加权融合算法;能够更好地适应当今大数据环境下对数据精确度的要求.     

水泥预热器出口废气温度监测数据的融合方法

水泥预热器出口废气温度由多个传感器监测,当监测数据异常波动且范围较小时,故障传感器不易被发现,影响现场实时热效计算的准确度。针对该问题,提出一种自适应分批估计的数据融合方法。利用温度传感器的实际监测值与估计值的方差实时调节各传感器所占的权重系数,逐渐弱化误差较大的传感器对数据融合值的影响。自适应分批估计算法与算术平均值法的仿真实验对比结果表明:前者在现场数据小范围异常波动情况下,较后者更能融合出接近实际的温度值,适用于对预热器出口废气温度多传感器数据的融合处理。     

高精度故障电弧检测多传感器数据融合算法

 由于故障电弧的物理特性复杂, 且电路中存在与故障电弧波形相似的负载, 因此传统 检测故障电弧的方法误判率较高. 提出了一种多传感器数据融合算法, 用于提高故障电弧的检测精度. 该算法包括自适应加权融合算法和神经网络融合算法, 实现了对温度传感器、声音传 感器和弧光强度传感器所获取的传感信号的数据融合. 自适应加权融合算法克服了单个传感 器的不确定性, 实现了同质传感器中故障电弧特征的提取, 为神经网络融合算法提供了精确的测试样本数据; 神经网络融合算法可自行调整各类异质传感器的权重, 使故障电弧的辨识率更高. 实验结果表明, 该算法可有效提取故障电弧的特征, 辨识精度超过98%, 实现了高精度的故障电弧检测.     

分布式多传感器结构中的数据融合方法

在分布式结构中,为了提高单个传感器的测量精度,为数据处理打下基础,首先对每一个传感器进行时间上的分批估计,降低误差的影响,得到各个传感器的局部决策值;接着对方差超过一定数值的数据进行基于相对距离的再处理;最后在最优融合原则下,运行加权自适应算法对各个局部决策值进行融合.数据分析结果表明,处理后的数据更接近测量真实值.     

多传感器粒子滤波融合跟踪算法

对于非线性非高斯环境中的多传感器分布式状态估计问题,提出了一种基于二阶中心差分粒子滤波方法的融合跟踪算法.通过对量测方程的非线性分析,利用粒子滤波器计算目标状态估计值,以在线自适应加权融合算法的方式得到系统最优估计.仿真结果表明,与采用扩展卡尔曼滤波的方法相比,该算法具有更高的估计精度.     

面向智能船舶的自校正加权融合估计算法

针对智能船舶多传感器系统因未知海洋环境干扰和设备间干扰等因素,导致一个或数个传感器产生间歇性随机故障,进而导致融合估计结果出现偏差甚至失真的问题,设计了一种自适应加权融合估值算法,并引入了衰减记忆因子降低旧测量数据对融合估计的影响权重.为增强融合估值器对于量测故障信号的容错性,添加了故障检测与校正模块对量测信号进行检测与校正.为了验证算法的容错性能和融合估计的精度,对带有间歇性随机故障的三传感器系统进行了仿真实验,并与改进前的自适应加权融合结果进行了对比.结果表明:对于带间歇性随机故障的多传感器系统而言,设计的自校正加权融合估计算法不仅具有鲁棒性,而且具有较高的融合精度.     

OFDM系统中基于子空间加权的时延估计算法

针对低信噪比条件下正交频分复用（orthogonal frequency division multiplexing，OFDM）系统利用MUSIC算法（multiple signal classification）进行时延估计时，特征值分解得到的信号子空间和噪声子空间不能完全正交导致算法性能下降的问题，提出一种基于子空间加权的时延估计算法——WMUSIC算法（weighted multiple signal classification）。算法对信道频域响应估计的协方差矩阵进行特征分解，利用噪声特征值的幂级数对噪声子空间进行加权处理，同时采用信号特征值的倒数对信号子空间进行加权处理，以修正MUSIC算法的伪谱，通过谱峰搜索得到时延估计值。仿真结果表明，与MUSIC算法相比，WMUSIC算法具有更高的时延估计精度，在信噪比为－8 dB时，估计精度在两径条件下提升71.46%，三径条件下提升19.48%。WMUSIC算法有效解决了低信噪比条件下MUSIC 算法伪谱谱峰存在混叠导致谱峰搜索误差较大的问题，可以完成较为准确的时延估计任务，提高了低信噪比条件下OFDM系统的时延估计性能。     

基于不确定度量化加权的CKF算法

针对传感器网络中每个传感器节点的邻接节点状态估计值不确定度不同的问题,提出一种基于不确定度量化加权的一致性卡尔曼滤波算法(CKF).该算法通过考虑节点度数对于传感器网络估计精度的影响,结合节点度数提出了一种衡量邻接节点状态估计值不确定度的量化函数,并把量化值作为该邻接节点与当前节点的状态估计值偏差的融合权重引入一致性协议中,利用优化后的一致性协议对传感器节点先验估计值进行更新,可提高一致性卡尔曼滤波算法的估计精度;算法同时具有非一致性误差小和鲁棒性强等特点.最后在3种不同网络类型下,通过动态目标跟踪实验仿真验证了算法的有效性.     

一种基于带监督局部保持投影的多模型软测量建模方法

针对化工生产过程中软测量模型估计精度的问题,提出了一种基于多知识库挖掘理论的带监督的局部保持投影(SLPP)方法。该方法用SLPP算法对输入数据空间进行类与类之间的降维,得到不同的类别转换矩阵和不同的类别多知识库,最后融合支持向量机自适应地实现组合建模。仿真结果表明:该建模方法用于双酚A含量的软测量建模中,较传统多模型方法可以更加合理地加权得到子模型,提高了模型估计精度,具有更强的泛化能力。     

分布式传感器网络中基于数据融合的目标定位算法研究

利用分布式传感器网络以及数据融合方法来提高探测系统的检测与定位精度正在成为研究的热点。提出了一种应用于分布式传感器网络中的数据融合算法,通过对各个传感器节点的定位信息的加权求和来进行数据融合,用来提高探测系统目标定位的精度。算法采用两级自适应调整得到最优加权因子。首先利用线性最小方差估计(LMSE)算法得到权系数的初始值,然后利用训练节点和递归最小二乘(RLS)算法自适应地调整达到最优。对静态和运动目标的定位数据融合算法进行了仿真。仿真结果表明,相比单节点定位,融合算法的定位精度有约一到两个数量级的提高。     

Markedness and its Interpretation in Language Use

Language markedness is a common phenomenon in languages, and is reflected from hearing, vision and sense, i.e. the variation in the three aspects such as phonology, morphology and semantics. This paper focuses on the interpretation of markedness in language use following the three perspectives, i.e. pragmatic interpretation, psychological interpretation and cognitive interpretation, with an aim to define the function of markedness.     

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.     

Features of Women's language

Language is a means of verbal communication. People use language to communicate with each other. In the society, no two speakers are exactly alike in the way of speaking. Some differences are due to age, gender, statue and personality. Above all, gender is one of the obvious reasons. The writer of this paper tries to describe the features of women＇s language from these perspectives： pronunciation, intonation, diction, subjects, grammar and discourse. From the discussion of the features of women＇s language, more attention should be paid to language use in social context. What＇s more, the linguistic phenomena in a speaking community can be understood more thoroughly.     

A computer generator for randomly layered structures

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

低渗透非均质砂岩油藏启动压力梯度研究

理论推导与室内实验相结合,建立了低渗透非均质砂岩油藏启动压力梯度确定方法。首先借助油藏流场与电场相似的原理,推导了非均质砂岩油藏启动压力梯度计算公式。其次基于稳定流实验方法,建立了非均质砂岩油藏启动压力梯度测试方法。结果表明:低渗透非均质砂岩油藏的启动压力梯度确定遵循两个等效原则。平面非均质油藏的启动压力梯度等于各级渗透率段的启动压力梯度关于长度的加权平均;纵向非均质油藏的启动压力梯度等于各渗透率层的启动压力梯度关于渗透率与渗流面积乘积的加权平均。研究成果可用于有效指导低渗透非均质砂岩油藏的合理井距确定,促进该类油藏的高效开发。     

On Tragic Consciousness In The Works By Ernest Hemingway

As an American modern novelist who were famous in the literary world, Hemingway was not a person who always followed the trend but a sharp observer. At the same time, he was a tragedy maestro, he paid great attention on existence, fate and end-result. The dramatis personae's tragedy of his works was an extreme limit by all means tragedy on the meaning of fearless challenge that failed. The beauty of tragedy was not produced on the destruction of life, but now this kind of value was in the impact activity. They performed for the reader about the tragedy on challenging for the limit and the death.     

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。     

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.     

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

正~~     

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