不均衡数据集中KNN分类器样本裁剪算法

针对KNN算法在分类时的样本相似度计算开销大,在处理不均衡数据集时少数类分类误差大的问题,提出一种在不均衡数据集下基于密度的训练样本裁剪算法。对训练样本的各个样本类进行聚类,删除噪声数据并计算每个样本类的平均相似度和样本平均密度,以此获得样本类裁剪的相似度阈值,然后将样本类内相似度小于类相似度阈值的样本进行合并,减少训练样本总数。实验表明,此样本裁剪算法能够在保持KNN算法分类性能基本稳定的前提下,有效地减少分类计算开销,并能在一定程度上提高少数类的分类性能。     

基于核可能性c-均值算法的支持向量机

提出一种基于核可能性c-均值算法的支持向量机分类算法,该算法改进了SVM训练过程中噪声和孤立点的敏感问题.其基本思想是:用核可能性c-均值算法对每个模式类训练样本进行聚类,得到不同的可能性度量值,根据得到的可能性度量值对训练样本进行修剪,删除具有较低可能性度量值的训练样本,最后用生成的新训练样本训练支持向量机.实验结果表明,该算法可以有效地解决由噪声和孤立点引发的分类错误问题以及重要样本的错分问题.     

基于密度的KNN分类器样本裁剪算法

KNN算法在分类准确率和召回率方面具有较好的性能,但由于样本相似度计算开销大,导致分类效率低.针对此问题,本文提出一种基于密度的训练样本裁剪算法,对训练样本的各个样本类进行聚类,根据密度不同聚集成不同的簇,删除噪声数据并计算每个样本类的相似度阈值,然后将样本类内大于类相似度阈值的样本进行合并,以减少训练样本总数.实验表明,此样本裁剪算法能够在保持KNN算法分类性能基本稳定的前提下,实现各个样本类内高相似度样本的合并,减少分类计算开销.     

一种改进的数据挖掘模糊支持向量机分类算法

针对模糊支持向量机(FSVM)应用于数据挖掘分类中存在对大样本集训练速度及分类速度慢的缺点,提出一种改进的数据挖掘模糊支持向量机分类算法.该算法首先预选有效的候选支持向量缩减训练样本集的规模提高训练速度;其次提出一种新的模糊隶属度函数,增强支持向量对构建模糊支持向量机最优分类超平面的作用,并用经过预选的训练样本集进行训练FSVM得到支持向量集;最后,运用粒子群优化算法选择最优支持向量子集,使用平均分类误差作为适应度函数,最终粒子输出时,将样本隶属度与设定阈值相比较,选择出支持向量集中相对较大隶属度的样本作为新的支持向量,提高分类速度.实验结果表明,该算法在不损失分类精度的情况下,提高了模糊支持向量机的训练速度和分类速度.     

一种改进的基于密度聚类的支持向量机

运用OPTICS算法能发现任意形状的聚类,且对输入参数不敏感的优势,提出一种基于OPTICS密度聚类的支持向量机算法,通过对原始数据进行预处理,利用可达图得到约简样本代替原始训练样本用支持向量机进行训练,降低了SVM训练所需的时间及空间复杂度.实验表明,该方法在保持分类精度的同时,大大缩短了训练时间,提高了分类效率.     

用于不平衡数据分类的模糊支持向量机算法

作为一种有效的机器学习技术,支持向量机已经被成功地应用于各个领域.然而当数据不平衡时,支持向量机会产生次优的分类模型;另一方面,支持向量机算法对数据集中的噪声点和野点非常敏感.为了克服以上不足,提出了一种新的用于不平衡数据分类的模糊支持向量机算法.该算法在设计样本的模糊隶属度函数时,不仅考虑训练样本到其类中心距离,而且考虑样本周围的紧密度.实验结果表明,所提模糊支持向量机算法可以有效地处理不平衡和噪声问题.     

基于改进FSVM的数据挖掘分类算法

针对模糊支持向量机(FSVM)应用于数据挖掘分类中存在对大样本集训练速度慢以及对噪声点敏感影响分类正确率的问题,提出一种基于改进FSVM的数据挖掘分类算法.该算法首先预选有效的候选支持向量,减小训练样本数目,提高训练速度;其次定义一种新的隶属度函数,增强支持向量对构建模糊支持向量机的作用;最后将近邻样本密度应用于隶属度函数设计,降低噪声点或野值点对分类的影响提高分类正确率.实验结果表明,该算法在训练样本数目较大时训练速度和分类正确率都有提高.     

一种基于动态类中心模型选择的模糊支持向量机

模糊支持向量机的核心思想是赋予样本模糊隶属度,给每个样本以不同的权重,从而克服标准支持向量机对噪声和异常点敏感的问题.现有的模糊支持向量机算法通常以样本与类中心距离为基础,给每个样本赋予一个固定的隶属度,没有根据样本分布对隶属度做进一步修正.提出了一种新的动态方式赋予样本隶属度,利用萤火虫算法不断地更新样本中心的位置和隶属度函数,同时利用粒子群算法优化模糊支持向量机参数.在UCI数据集上的实验结果表明,该算法可以有效减少噪声和野点对超平面的影响,分类性能要优于几类常用的模糊支持向量机算法.     

基于DLSVM算法的高分辨率遥感图像分类研究

为了进一步提高高分辨率遥感图像的分类精度及效率,融合支持向量机SVM及局部支持向量机KNNSVM算法,借助主动学习相关理论,提出了基于距离的局部支持向量机算法(DLSVM).该算法通过对未标记样本和超平面之间的距离与预先设定的距离阈值相比较,判断是否需要进一步建立局部支持向量机KNNSVM来确定样本的类标.对实际的高分辨率遥感图像分类的实验结果显示:在合适的距离阈值与K值的设置下,该算法能够提高支持向量机SVM的分类精度,同时大大降低KNNSVM算法的时间消耗.     

一种新的支持向量机增量学习算法

支持向量机学习算法的本质是从训练集中寻找支持向量,因此能否通过训练算法能快速找出支持向量是衡量支持向量机算法优劣的重要标准.本文提出了一种新的快速训练支持向量机的增量学习算法,首先,给出边界向量的定义,然后,对一个给定的新加人的样本,新的学习方法验证其是否为边界向量,如果是,将其加入到训练集中重新训练支持向量机,如果不是,就舍弃,这样能达到减少训练样本、降低训练复杂性目的,最后,给出了一个增量学习算法.实验表明测试误差和支持向量数量与SMO算法大致相当,而训练速度明显加快.     

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-