基于知识量加权的直觉模糊均值聚类方法

针对聚类算法中特征数据对聚类中心贡献的差异性及算法对初始聚类中心的敏感性等问题,提出一种基于知识量加权的直觉模糊均值聚类方法。首先将原始数据集直觉模糊化并改进最新的直觉模糊知识测度计算知识量,据此实现数据集特征加权,再利用核空间密度与核距离初始化聚类中心,以提高高维特征数据集的计算精度与聚类效率,最后基于类间样本距离与最小知识量原理建立聚类优化模型,得到最优迭代算法。基于UCI人工数据集的实验结果表明,所提方法较大程度地提高了聚类的准确性与迭代效率,分类正确率及执行效率分别平均提高了10.63%和31.75%,且具有良好的普适性和稳定性。该方法首次将知识测度新理论引入模糊聚类并取得优良效果,为该理论在其他相关领域的潜在应用开创了新例。     

一种基于谱聚类的灰度图像分割法

针对传统模糊核聚类算法当数据类差别很大时,小数据类被误分或被大数据类吞并的缺陷,提出了一种新的加权模糊核C 均值聚类算法(Weighted Fuzzy Kernel C-Means),为每一个类分配了一个动态权值;同时将该算法引入到谱聚类中,设计了一个以图像灰度特征作为分类样本的改进的谱聚类算法,解决了谱聚类应用于图像分割时权矩阵的谱难以计算的实际问题。实验结果表该算法具有较好的分割效果。     

动态加权模糊核聚类算法

为了克服噪声特征向量对聚类的影响,充分考虑各特征向量对聚类结果的贡献度的不同,运用mercer核将待聚类的数据映射到高维空间,提出了一种新的动态加权模糊核聚类算法.该算法运用动态加权,自动消弱噪声特征向量在分类中的作用,在对数据没有任何先验信息的情况下,不仅能够准确划分线性数据,而且能够做到非线性划分非团状数据.仿真和实际数据分类结果表明,数据中的噪声对分类结果影响较小,该算法具有很高的实用性.     

基于K近邻加权的混合C均值聚类算法

该文提出了一种基于K近邻加权的混合C均值聚类算法。首先该文利用模糊C均值聚类和可能性C均值聚类的优点,设计出一种混合C均值聚类算法。然后以K近邻规则为基础,计算出样本集的加权矩阵,最后得到基于K近邻加权的混合C均值聚类算法。由于该算法考虑到了不同样本点对分类的影响程度,对较复杂的样本集合,能明显提高分类的正确性和鲁棒性。     

基于特征加权K-means聚类的多模型软测量建模

针对传统K-means聚类算法的聚类结果易随不同的初始聚类中心波动的问题,采用最大距离积法优化K-means聚类算法的初始聚类中心。传统的K-means聚类算法都假定样本的各维特征对聚类的贡献相同,影响了聚类效果和模型估计精度。为了考虑样本各维特征对聚类的不同影响,利用一种新型的特征加权K-means聚类算法逐步调整特征权值,最终有效改善了聚类效果。利用本文方法建立组合支持向量机模型,将其用于双酚A生产过程质量指标的软测量建模中,仿真结果表明该算法能够有效改进数据的分类效果并提高软测量模型的估计精度。     

一种基于数据流的软子空间聚类算法

针对高维数据的聚类研究表明,样本在不同数据簇往往与某些特定的数据特征子集相对应.因此,子空间聚类技术越来越受到关注.然而,现有的软子空间聚类算法都是基于批处理技术的聚类算法,不能很好地应用于高维数据流或大规模数据的聚类研究中.为此,利用模糊可扩展聚类框架,与熵加权软子空间聚类算法相结合,提出了一种有效的熵加权流数据软子空间聚类算法——EWSSC(entropy-weighting streaming subspace clustering).该算法不仅保留了传统软子空间聚类算法的特性,而且利用了模糊可扩展聚类策略,将软子空间聚类算法应用于流数据的聚类分析中.实验结果表明,EWSSC 算法对于高维数据流可以得到与批处理软子空间聚类方法近似一致的实验结果.     

基于成对约束的动态加权半监督模糊核聚类

针对样本间的不均衡性,提出一种基于成对约束的动态加权半监督模糊核聚类算法。在传统模糊聚类算法中加入半监督学习机制,通过Mercer核将原数据空间映射到特征空间,为特征空间中的每个向量分配一个动态权值,由此得到新的目标函数,并结合一种简单的核参数选择方法实现数据分类。理论分析和实验结果表明,与模糊核聚类算法及成对约束的竞争群算法相比,该算法具有更好的聚类效果。     

基于特征加权距离的双指数模糊子空间聚类算法

传统的模糊聚类算法(FCM)使用欧氏距离计算数据点之间的差异时,对于高维数据集聚类效果不够理想.对此,以FCM算法的目标函数为基础,用特征加权距离代替传统的欧氏距离,同时向约束条件中引入指数γ和β,提出了一种基于特征加权距离的双指数模糊子空间聚类算法,并讨论了该算法的收敛性.实验表明,所提出算法可以有效提取高维数据集各类别的相关特征,在真实数据集上有较好的聚类效果.     

一种特征加权的聚类算法框架

为了考虑数据各维特征对聚类的不同贡献,并把有监督特征评价方法应用到无监督分类问题中,提出一种特征加权的聚类算法框架.该框架首先通过某种聚类算法对数据聚类,然后,根据聚类结果,采用有监督特征评价方法学习各维特征的权值,再根据特征权值重新聚类,之后再次学习特征权值,该过程反复迭代,直至算法收敛或达到指定的迭代次数.欧几里德空间内基于距离、基于密度的聚类算法均适用于本框架.基于本框架,采用模糊C均值聚类算法(FCM)、密度聚类算法(DBSCAN),并通过信息增益特征评价、ReliefF特征评价方法,对多个UCI数据集进行了实验,验证了该框架的有效性.     

一种适用于基因表达数据的特征加权FCM算法*

针对FCM算法应用于基因表达数据分析时存在的局限性,提出一种特征加权自适应FCM算法。该算法在FCM算法的基础上引入数据集预处理机制,可依据数据集的分布特征自适应地获取分类数目和初始聚类中心,并通过ReliefF算法实现特征权值的自动确定。同时,新算法考虑了不同属性对分类贡献的差异,在FCM算法中引入特征权重。将算法应用于真实基因表达数据集,实验结果表明,算法能够自适应地确定聚类数目、获得稳定性较好的聚类结果,而且具有较高的聚类精度。     

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。     

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.     

Enhancing a leaf radiative transfer model to estimate concentrations and in vivo specific absorption coefficients of total carotenoids and chlorophylls a and b from single-needle reflectance and transmittance

The relative concentrations of different pigments within a leaf have significant physiological and spectral consequences. Photosynthesis, light use efficiency, mass and energy exchange, and stress response are dependent on relationships among an ensemble of pigments. This ensemble also determines the visible characteristics of a leaf, which can be measured remotely and used to quantify leaf biochemistry and structure. But current remote sensing approaches are limited in their ability to resolve individual pigments. This paper focuses on the incorporation of three pigments—chlorophyll a, chlorophyll b, and total carotenoids—into the LIBERTY leaf radiative transfer model to better understand relationships between leaf biochemical, biophysical, and spectral properties.Pinus ponderosa and Pinus jeffreyi needles were collected from three sites in the California Sierra Nevada. Hemispheric single-leaf visible reflectance and transmittance and concentrations of chlorophylls a and b and total carotenoids of fresh needles were measured. These data were input to the enhanced LIBERTY model to estimate optical and biochemical properties of pine needles. The enhanced model successfully estimated reflectance (RMSE = 0.0255, BIAS = 0.00477, RMS%E = 16.7%), had variable success estimating transmittance (RMSE = 0.0442, BIAS = 0.0294, RMS%E = 181%), and generated very good estimates of carotenoid concentrations (RMSE = 2.48 µg/cm², BIAS = 0.143 µg/cm², RMS%E = 20.4%), good estimates of chlorophyll a concentrations (RMSE = 10.7 µg/cm², BIAS = − 0.992 µg/cm², RMS%E = 21.1%), and fair estimates of chlorophyll b concentrations (RMSE = 7.49 µg/cm², BIAS = − 2.12 µg/cm², RMS%E = 43.7%). Overall root mean squared errors of reflectance, transmittance, and pigment concentration estimates were lower for the three-pigment model than for the single-pigment model. The algorithm to estimate three in vivo specific absorption coefficients is robust, although estimated values are distorted by inconsistencies in model biophysics. The capacity to invert the model from single-leaf reflectance and transmittance was added to the model so it could be coupled with vegetation canopy models to estimate canopy biochemistry from remotely sensed data.     

Mr. Twinn’s bombes

This article discusses the history and design of the special versions of the bombe key-finding machines used by Britain’s Government Code & Cypher School (GC&CS) during World War II to attack the Enigma traffic of the Abwehr (the German military intelligence service). These special bombes were based on the design of their more numerous counterparts used against the traffic of the German armed services, but differed from them in important ways that highlight the adaptability of the British bombe design, and the power and flexibility of the diagonal board. Also discussed are the changes in the Abwehr indicating system that drove the development of these machines, the ingenious ways in which they were used, and some related developments involving the bombes used by the U.S. Navy’s cryptanalytic unit (OP-20-G).