模糊聚类在中文文本分类中的应用研究

将基于等价关系的模糊聚类技术应用于中文文本分类,提出了基于模糊聚类的中文文本分类算法ATCFC。该算法利用基于二级字索引的正向最大匹配算法对文本分词,建立模糊特征向量空间模型,使用贴近度法刻划文本间的相似度。利用算法ATCFC对文本集合进行动态聚类实验,实验结果表明算法ATCFC对于中文文本分类是可行、有效的。     

模糊K-Modes聚类精确度分析

模糊K-Modes聚类算法是对具有分类属性的数据进行聚类的一种有效的算法。为了评价聚类结果，以具有明确分类结构的数据作为输入数据，将模糊K-Modes聚类结果与原始数据的分类结构进行对比，分析了确定它们之间对应关系的方法，在期望聚类结果应该具有的特点的基础上，对现有的精确度定义和计算方法进行修正，在划分相似度的基础上，重新定义模糊K-Modes聚类精确度。     

基于直觉模糊包含度的聚类有效性分析

针对直觉模糊集合数据的聚类有效性问题,提出了一种基于直觉模糊包含度的聚类有效性分析方法。该方法采用直觉模糊包含度和直觉模糊划分熵来评价直觉模糊聚类的有效性。其中,直觉模糊包含度通过增加非隶属度参数对模糊包含度进行直觉化扩展,用于评价类与类间包含的程度;而直觉模糊划分熵用于检验分类结果的可靠性。最后通过典型实例验证了该方法的有效性。     

基于犹豫模糊决策树的非均衡数据分类

为优化针对非均衡数据的分类效果,结合犹豫模糊集理论与决策树算法,提出一种改进的模糊决策树算法。通过SMOTE算法对非均衡数据进行过采样处理,使用K-means聚类方法获得各属性的聚类中心点,利用2种不同的隶属度函数对数据集进行模糊化处理。在此基础上,根据隶属度函数和犹豫模糊集的信息能量求得各属性的犹豫模糊信息增益,选取最大值替代Fuzzy ID3算法中的模糊信息增益作为属性的分裂准则,构建一个用于非均衡数据分类的犹豫模糊决策树模型。实验结果表明,基于犹豫模糊决策树的分类器在AUC评价指标上相对于C4.5、KNN、随机森林等传统分类算法平均提高了12.6%。     

基于模糊C均值聚类的多分量彩色图像分割算法

以模糊C均值(FCM)聚类理论为基础,选用符合人眼视觉特性的HSI颜色空间,提出了一种新的多分量彩色图像分割算法。该算法首先结合数据分布特点确定出H分量与I分量的初始聚类中心;然后利用FCM聚类技术对H分量、I分量进行分类处理,以得到不同分量的像素点隶属度;最后,将所得到的不同分量像素点隶属度组织成2维特征,并以此进行模糊聚类图像分割。实验结果表明,该算法可有效提高图像分割效果,其分割结果优于传统FCM聚类图像分割方案。     

一种新的模糊支持向量机

基于类中心设计隶属度函数的模糊支持向量机能有效地解决支持向量机对噪声或孤立点敏感度高的问题,但是,由于它对支持向量赋予较小的隶属度,从而降低了其分类作用。基于此,提出一种新的隶属度函数设计方法;同时,针对模糊支持向量机普遍存在因核函数计算量大,而导致训练时间长的问题,通过使用一种高效的截集模糊C-均值聚类方法对训练样本进行聚类,然后以聚类中心作为样本进行训练,以减少训练样本来提高训练速度。根据上述新的隶属度函数设计方法和截集模糊C-均值聚类方法,构建了一种基于截集模糊C-均值聚类并改进了隶属度函数的模糊支持向量机,数值试验表明这种新的模糊支持向量机有效地提高了训练速度和分类精度。     

具有强解释性的贝叶斯MA型模糊系统

提出用于规则前件学习的中心点交叉涌现的大间隔贝叶斯模糊聚类(CECLM-BFC)算法.考虑不同样本间聚类中心的排斥作用使得聚类中心间距最大化,并采用粒子滤波方法在不同类别样本中交替执行,自动求解出最优聚类结果,包括聚类数、模糊隶属度和聚类中心.在模糊规则后件参数学习上使用分类面大间隔的策略,以MA型模糊系统为研究对象构造具有强解释性的贝叶斯MA型模糊系统(BMA-FS).实验结果表明,BMA-FS能够取得令人满意的分类性能,且模糊规则具有高度的解释性.     

靶场测量中跟踪目标的多尺度多级模糊聚类分类算法

靶场测量中的连发弹目标数量较多,需要对此目标进行分类跟踪,文章提出了一种多尺度多级模糊聚类的分类算法,首先对靶场测量中的多连发目标的特性进行分析,定义了3种不同的类目标群序列,其次针对模糊聚类算法必须先验确定聚类初始点以及聚类中心的缺陷,在此基础上加入尺度因子,并根据目标群的位置信息以及运动方向信息进行多级聚类,最后通过多次聚类实验证明分类结果能够满足靶场测量中的多连发目标的分类要求.     

基于支持向量机的模糊系统辨识研究

GK模糊聚类是一类广泛应用于分类的数据分析技术,能智能探测不同聚类的形状,但是存在迭代过程中聚类数恒定、公式中协方差矩阵要求非零等缺点。本文针对这些缺点,提出改进的聚类算法,针对现有的模糊辨识算法出现的维数灾难及函数逼近能力不高等问题,以语言模糊模型和缺少常数项的支持向量回归机的等价性分析为基础,提出一种支持向量机与模糊系统相结合的新辨识算法,并且利用梯度下降法对参数进行辨识;为了更好地缩减规则数及体现样本数据的信息,对输入的样本集又采用改进的GK模糊聚类对数据进行分类。     

应用分类方法进行聚类评价*

针对现有基于几何结构的聚类有效性指标不能有效解决不同结构数据的聚类结果评价问题,提出了一种使用分类对聚类结果进行评价的方法。该方法把聚类得到的对象类标志作为分类问题的已知类标志,使用交叉验证法对数据集重新分类,通过对比聚类结果与分类结果之间的差异来衡量聚类有效性。一个易于聚类的数据集的结构意味着也容易进行分类,对模拟数据和真实数据的实验和分析验证了该方法的可行性和有效性。     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.     

Editorial: Special issue on recent advances in hybrid control theory and applications

正The demands of a rapidly advancing technology for faster and more accurate controllers have always had a strong influence on the progress of automatic control theory.In recent years control problems have been arising with increasing frequency in widely different areas,which cannot be addressed using conventional control techniques.The principal reason for this is the fact that a highly competitive economy is forcing systems to operate in regimes where     

Information for Authors

正Aim The Journals of Zhejiang University-SCIENCE(A/B/C)areedited by the international board of distinguished Chinese andforeign scientists,and are aimed to present the latest devel-opments and achievements in scientific research in China andoverseas to the world’s scientific circles,especially to stimulateand promote academic exchange between Chinese and for-eign scientists everywhere.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.