基于PCA的RBF神经网络预测方法研究

主成分分析(PCA)法可以提取样本集的主成分,实现样本的最优压缩,从而降低样本的维数。针对用RBF神经网络进行多因素时间序列预测时样本特征指标过多的问题,提出用统计理论的PCA方法对数据进行预处理,再选出几个主成分作为神经网络的输入节点.仿真实验表明,基于PCA的RBF神经网络模型在拟合预测中与一般的RBF神经网络模型相比有较好效果,简化了网络结构,改善了预测精度.     

基于PCA与RBF的建筑能耗预测建模

由于建筑能耗因子间存在非线性和高度冗余特性,传统预测方法很难消除数据之间冗余和捕捉非线性特征,导致预测精度较低.为了提高建筑能耗预测精度,提出一种将主成分分析(principal component analysis,PCA)和径向基函数(radial basic function,RBF)神经网络相结合的建筑能耗预测方法(PCA-RBF).利用PCA消除建筑能耗高维变量数据的相关性,并按累积贡献率提取主成分,将主成分作为RBF神经网络的输入进行训练学习.通过PCA避免了模型过多的输入导致的训练耗时长及预测精度较低的不足.通过将PCA-RBF模型方法应用于某办公建筑能耗的预测中,并与RBF神经网络及BP神经网络模型相比,实验结果表明PCARBF模型方法能有效提高建筑能耗预测精度.     

BM-MSCs的CNN特征映射与活性评价模型研究

针对分选富集具有治疗疾病效果的干细胞(MSCs)亚群很难实现质量控制的问题,设计了以深度神经网络作为特征映射的主成分分析-岭回归模型,实现对骨髓间充质干细胞(BM-MSCs)的定量评价.通过三维重建细胞计算基于长轴的最大截面作为模型输入;训练4层神经网络将细胞分为正常细胞与病人细胞,提取全连接层输出作为特征映射;利用主成分分析降维后的前3项主成分向量作为自变量X,样本评分作为因变量Y,使用岭回归模型进行拟合,将特征与细胞活性评分相联系,实现BM-MSCs活性定量评价,为后续分选高质量的活性细胞提供依据.第1阶段通过对176例细胞样本进行数据扩增,采用8折交叉验证输入二分类神经网络进行训练,第2阶段将其中标有专家评分的68例细胞样本输入到已训练的神经网络中提取全连接层输出作为特征,利用主成分分析-岭回归模型实现定量评价,结果表明:神经网络二分类准确率98.75%,敏感度为97.84%,特异度为99.43%,对于定量评价,模型总体样本的R2为0.873 6,拟合效果良好,可以实现对BM-MSCs定量评价.     

PCA支持向量机回归集成股市预测应用

利用主成分分析（PCA）方法优选神经网络集成个体,利用支持向量机回归集成生成输出结论,建立一个PCA支持向量机回归集成股市预测模型。试验表明,该模型能有效提高神经网络集成系统的泛化能力,预测精度高,稳定性好。     

基于深度学习MPCANet的年龄估计

提出了一种基于多层PCA网络(MPCANet)的深度学习模型来进行年龄估计.它是基于卷积神经网的结构来设计的,并且用来提取年龄特征.MPCANet是主成分分析网络(PCANet)的一种改进,它是最近提出的一种深度学习算法,MPCANet模型结构组成的成分:(1)卷积滤波层是采用多层级联主成分分析(PCA),(2)非线性层则采用二进制哈希,(3)特征抽取层使用直方图统计方法.使用核支持向量回归(K-SVR)进行估计年龄值.实验分别在两个数据库(FG-NET and MORPH)上进行,实验结果表明该方法比目前最新的方法表现得更好.     

优化NARX神经网络对时间序列溶解氧的预测

为提高非线性有源自回归(NRAX)神经网络模型的预测精准度,采用主成分分析(PCA)法和灰色关联分析(GRA)法提取原始数据特征并减少输入变量的维度,通过构建PCA-NARX和GRA-NARX模型预测地表水体未来短期(48 h)溶解氧(DO)的质量浓度.结果表明:GRA-NARX模型对时间序列DO质量浓度的预测效果优于...     

基于PCA-LVQ神经网络的教学质量评价模型研究

为了进一步提高教学质量评价准确率,提出一种基于主成分分析(PCA)和学习矢量量化神经网络(LVQ)相结合的教学质量评价模型.使用层次分析法(AHP)建立教学质量评价体系,再用主成分分析提取初始评价指标体系的特征信息,将经过降维处理后的特征信息输入到LVQ神经网络,并对网络模型进行训练和泛化能力测试.实验结果表明,与单一的LVQ和BP神经网络相比,PCA-LVQ网络模型的结构更为简化,学习能力更强,收敛速度更快,评价准确率更高且泛化能力强.     

基于PCA和BP网络的液压油缸内泄漏故障诊断

针对液压油缸内泄漏故障诊断时,由于提取的时域参数过多,导致诊断速度慢、实时性差等问题,提出基于主成分分析(PCA)和BP神经网络的诊断方法.该诊断方法是:首先提取压力信号的时域参数作为初始特征,然后利用PCA方法将高维初始特征空间压缩到低维最终特征空间,并将得到的最终特征输入到BP神经网络进行故障模式识别.研究结果表明:该诊断方法在满足故障检测识别率的同时提高了诊断速度,为液压油缸内泄漏的故障诊断提供了一种实用方法.     

基于多维度光谱特征波长提取大豆冠层SPAD值估算模型

应用多种光谱特征波长段提取技术,研究了全生育期大豆冠层的近红外光谱曲线特性,提出了基于多维度光谱特征波长提取的大豆冠层叶绿素相对含量(SPAD值)估算模型.在大豆冠层原始近红外光谱曲线中,优选多元散射校正预处理和偏最小二乘回归法建模.经多元散射校正预处理后,应用竞争性自适应重加权采样算法(CARS)、主成分分析法(PCA)和连续投影算法(SPA),提取大豆冠层的光谱特征波长数量分别为22,51和12个.以此特征波长为基础,利用偏最小二乘回归法和多元线性回归法(MLR),分别建立大豆冠层SPAD值估算模型.结果表明CARS-MLR模型试验效果较好,该模型校正样本和预测样本SPAD值的均方根误差分别为5.67和5.94,平均值约为5.81.     

基于主分量分析的形状特征提取及识别研究

主分量分析(PCA)是统计学中分析数据的一种有效的方法,可以将数据从高维数据空间变换到低维特征空间,因而可以用于数据的特征提取及压缩等方面。在该文的形状识别系统中,用PCA法提取图像的形状特征,能够较好地满足识别层的输入要求。在识别层研究了3种识别方法:最近邻法则、BP网络及协同神经网络方法,均取得了满意的实验效果。     

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.     

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.     

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.     

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.     

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.     

Jane Eyre——A Feminist In The 19th Century

In the 19th century the society was controlled by men, and women were just appendants of them, they had not any rights and freedom. But Jane was an exception, she showed some characteristics of early feminist. Jane showed her characteristics of feminism in three aspects: rebellion, equality, and independence. These characteristics were helpful to her success, and feminism is the only way out for women of that time.     

Achieving Unusual States of Matter Under High Pressure

正The periodicity of the elements and the non-reactivity of the inner-shell electrons are two related principles of chemistry,rooted in the atomic shell structure.Within compounds,Group I elements,for example,invariably assume the+1 oxidation state,and their chemical properties differ completely from those of the p-block elements.These general rules govern our understanding of chemical structures and reactions.Using first principles calcula-     

Exchange-Correlation and Electronic Excitation Energies from Pairing Matrix Fluctuations

We have developed an adiabatic connection to formulate the ground-state exchange-correlation energy in terms of pairing matrix linear fluctuations.This formulation of the exchange-correlation energy opens a new channel for density functional approximations based on the many-body perturbation theory.We illustrate the potential of such approaches with an approximation based on the particle-particle Random Phase Approximation(pp-RPA).This re-