基于阈值聚类和KNN分类的入侵检测

利用基于阈值聚类算法首先对带类标记的样本数据集进行有指导性聚类,其主要目的是压缩训练数据集,解决KNN分类算法的样本选择问题以及孤立点的发现,用少量的更具代表性的聚类中心替代KNN算法中巨大的样本集,然后利用聚类密度改进KNN分类算法,从而提高KNN分类检测的准确度和速度.     

基于超长方体与KNN的分类算法

提出了超长方体与KNN相结合的分类算法.在训练阶段,该算法为训练集中的每一个类别构造多个超长方体,区域分离每一类训练样本.在测试阶段,该算法首先检查测试样本是否被某一个超长方体包围,如是则其类别被识别出,否则用KNN方法确定其类别.实验采用四个真实数据集进行测试.实验结果表明基于超长方体与KNN的分类算法在四个数据集全部优于两个基于多球覆盖的分类方法,是一种有效的分类方法.     

基于Spark的大规模文本KNN并行分类算法

在使用KNN算法进行大规模文本分类,需要处理频繁的迭代运算,针对现有Hadoop平台迭代运算效率较低的问题,本文提出一种基于Spark平台的并行优化KNN算法.主要从3个方面对算法进行优化,首先,对于训练数据集通过剪枝算法控制有效数据的规模,从而减少迭代运算的次数;其次,针对高维数据集采用ID3算法利用信息熵进行属性降维,减少文本相似度的运算量;最后,使用Spark并行计算平台,引入内存计算最大限度地减少了迭代运算的I/O次数,提高处理速度.通过实验,与常用的KNN算法相比,基于Spark的KNN文本并行分类算法在加速比、扩展性等主要性能指标上表现较优,能够较好地满足大规模文本分类的需求.     

基于近邻决策域内局部分布密度的改进KNN算法

经典KNN算法和以往的基于密度的改进KNN算法都缺乏对训练样本数据分布的有效性描述,因此会间接影响到分类结果。提出一种基于测试样本近邻决策域内局部密度的改进KNN算法,通过计算各不同类别在近邻决策域内的局部密度,并同时考虑到类间偏斜度的存在,得到各类密度补偿系数和倾斜度平衡因子,从而达到削弱高数量、大密度类别,增强小数量、低密度类别的目的。在UCI数据集上的实验结果表明,该改进算法在保持经典KNN算法分类准确度的基础上,能够提高分类的召回率和F1-measure指标。     

一种基于KNN的半监督分类改进算法

本文提出一种新的基于KNN分类的半监督学习self-training改进算法,并以多个UCI数据集为实验,对基于KNN的半监督分类模型算法进行改进,充分利用已知类别标签数据的正确知识进行自训练,以得到最终分类结果.实验结果表明,该方法能显著提高分类准确率.     

基于模糊C-Means的改进型KNN分类算法

KNN算法是一种思想简单且容易实现的分类算法,但在训练集较大以及特征属性较多时候,其效率低、时间开销大.针对这一问题,论文提出了基于模糊C-means的改进型KNN分类算法,该算法在传统的KNN分类算法基础上引入了模糊C-means理论,通过对样本数据进行聚类处理,用形成的子簇代替该子簇所有的样本集,以减少训练集的数量,从而减少KNN分类过程的工作量、提高分类效率,使KNN算法更好地应用于数据挖掘.通过理论分析和实验结果表明,论文所提算法在面对较大数据时能有效提高算法的效率和精确性,满足处理数据的需求.     

基于聚类和密度裁剪的改进KNN算法

经典KNN算法在处理高维数据或样本数繁多的样本集时需要巨大的计算量,这使其在实际应用的过程中存在着一定的局限性;提出一种基于聚类和密度裁剪的改进KNN算法。在训练阶段,首先根据样本密度对整个训练集进行裁剪,然后将裁剪好的训练集进行聚类处理,得到若干个密度比较均匀的类簇并将其转化为超球。在测试阶段,采用两种方法,第一种是找出距离待测样本最近的k个超球,然后将这个k个超球内的训练样本作为新的训练样本集,在这个新的训练样本集上使用经典KNN算法得到待测样本的类别;第二种则是找出距离待测样本最近的1个超球,然后根据该超球的类别得出待测样本的类别。实验采用8个UCI样本集进行测试,实验结果表明,该算法同经典KNN相比具有良好的性能,是一种有效的分类方法。     

基于改进K最近邻算法的中文文本分类

针对文本分类存在的高维文本问题,提出文档频率(DF)-卡方统计量特征提取方式,对特征项进行有效约减,降低文本维度,提高分类精度.在K最近邻(KNN)算法的基础上,针对待分类文本需要和大量训练集样本进行相似度计算的问题,提出一种基于分组中心向量的KNN算法,对类别内的样本集分组求出各组中心向量,使其重新代表训练库计算相似度,降低计算复杂度,提升算法的分类性能.通过实验表明:相较传统KNN算法,改进的算法在准确率、召回率及F值方面都有提升,与其他分类算法相比,具有一定的优势.     

一种改进的基因表达数据分类方法

从分类算法和特征基因选择两个方面研究基因表达数据的分类,将传统的Support Vector Machines(SVM)算法和K-nearest neighbor(KNN)算法两者结合成为一种应用于基因表达数据分类的算法,并针对基因表达数据分类数据集“样本少,维数高”的特点,提出了一种改进的基于相关性的递归特征消除算法(简称为C-RFE),消除了数据冗余．实验结果表明,新方法可有效提高分类准确率和特征选取的效率．     

改进的KNN快速分类算法

传统的KNN算法的时间复杂度与样本规模成正比,大规模或高维数据会降低其分类效率。为此,提出一种改进的KNN快速分类算法。该算法以固定半径长度构造超球为原则,为训练样本集构造多个包围超球。根据各个超球内包含的训练样本集的重心位置与测试样本的位置关系可以快速搜索测试样本的k个最近邻超球,然后以k个最近邻超球内的训练样本集构造新的训练样本集。在新的训练样本集中求测试样本的k个最近邻,从而获得该测试样本的类别。实验表明,改进的KNN快速分类算法的分类准确率得到一定程度的提高、运行效率明显提升。     

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-