多路径测试数据自动生成方法及应用

以程序结构测试自动生成为研究背景,提出了一种重叠路径结构用以描述程序路径,并以此为基础设计了一种多路径测试数据生成适应值算法,实现了一次搜索完成多条路径的测试数据生成。算法通过目标路径间共享遗传算法产生的中间个体减少单一路径搜索始于随机产生的无序个体的初期迭代,从而加快搜索收敛的速度。应用于常用的基准程序和取自实际项目的程序,该算法与典型的分支谓词距离算法相比平均消耗时间缩短了70.6%。     

基于复杂属性相似度的聚类算法及其应用研究

针对电信客户的有效细分问题,利用属性相似度度量思想,提出了一种面向复杂属性的聚类算法。该算法用复杂属性分布相似度函数衡量对象的相似性,然后根据相似性建立图模型,最后对图进行分割进行聚类。相比于传统基于选维和降维的聚类分析算法,提出的算法能有效处理高维数据和复杂属性。同时,算法在参数调节时,不需遍历原始数据,也减少了人工干预。利用真实电信客户数据进行的模拟实验也表明,提出的算法具有良好性能,可以有效解决电信客户细分问题。     

The monotonic increasing relationship between average powers of CMOS VLSI circuits with and without delay and its applications

The authors theoretically describe the monotonic increasing relationship between average powers of a CMOS VLSI circuit with and without delay. The power of an ideal circuit without delay, which can be fast computed, has been used as the evaluation criterion for the power of a practical circuit with delay, which needs more computing time, in such fields as fast estimation for the average power and the maximum power, and fast optimization for the low test power. The authors propose a novel simulation approach that uses delay-free power to compact a long input vector pair sequence into a short sequence and then, uses the compacted one to fast simulate the average (or maximum) power for a CMOS circuit. In comparison with the traditional simulation approach that uses an un-compacted input sequence to simulate the average (or maximum) power, experiment results demonstrate that in the field of fast estimation for the average power, the present approach can be 6-10 times faster without significant loss in accur     

Clustering and aggregation of relational data with applications to image database categorization

In this paper, we introduce a new algorithm for clustering and aggregating relational data (CARD). We assume that data is available in a relational form, where we only have information about the degrees to which pairs of objects in the data set are related. Moreover, we assume that the relational information is represented by multiple dissimilarity matrices. These matrices could have been generated using different sensors, features, or mappings. CARD is designed to aggregate pairwise distances from multiple relational matrices, partition the data into clusters, and learn a relevance weight for each matrix in each cluster simultaneously. The cluster dependent relevance weights offer two advantages. First, they guide the clustering process to partition the data set into more meaningful clusters. Second, they can be used in subsequent steps of a learning system to improve its learning behavior. The performance of the proposed algorithm is illustrated by using it to categorize a collection of 500 color images. We represent the pairwise image dissimilarities by six different relational matrices that encode color, texture, and structure information.     

模糊超球神经网络在模式聚类中的应用

提出和实现了用于模式聚类的无监督模糊超球神经网络.模式集是一个具有超球核的用隶属函数表示的模糊集,模式集又可以合并成模式类.模糊超球神经网络学习算法能在几次循环学习中形成模式集,无需对已知模式集重新训练就可融合新样例和精炼已存在的模式集.模式聚类的数值仿真解释了模糊超球聚类神经网络的优越性能.     

基于.NET的题库管理系统设计与实现

试卷命题组卷是教学中的重要环节,然而教师以传统方式进行组卷时,劳动强度非常大,工作周期长,试卷质量难以保证。针对这种情况,提出运用.NET技术和SQL Server数据库,开发基于C/S模式的题库管理系统的方案,介绍了题库管理系统的功能模块、数据库实现、系统架构,阐述了其核心功能的详细实现过程。应用该系统,可以编辑课程、知识点、试题等信息,在设置总分、难度系数、题型等参数后按照一定约束条件进行组卷生成试卷。系统实际应用效果良好。     

数据聚类算法的改进及其应用

在分析和比较k平均分区算法和层次凝聚算法的基础上,提出了一种新的改进算法(NQ算法)。并以贵州民族学院近四年学生试卷数据作为测试数据,对NQ算法与k平均分区算法和层次凝聚算法进行了性能对比,实践证明:NQ算法是有效、可靠和快速的。     

基于聚类算法和层次支持向量机的人脸识别方法

提出一种基于聚类算法和层次支持向量机的人脸识别方法。该方法在训练阶段把利用小波变换提取的图像特征先进行聚类,再利用聚类的结果来训练层挺支持向量机;识别阶段先利用层次支持向量机初步判断待识别图像最可能所属的人,最后利用免疫算法对待识别的人脸图像进行确认。实验表明,该算法效果较佳。     

Improved method to generate path-wise test data

Gupta et al.,propsed a method ,which is referred to as the Iterative Relaxation Method ,to generate test data for a given path in a program by linearizing the predicate functions.In this paper,a model language is presented and the properties of static and dynamic data depen-dencies are investigated ,The notions in the Interative Relaxation Method are defined formally.The predicate slice proposed by Gupta et al.is extended to path-wise static slice.The correctness of the constructional algorithm is proved afterward The improvement shows that the constructions of predicate slice and input dependency set can be omitted .The equivalence of systems of constraints generated by both methods is proved ,The prototype of path-wise test data generator is presented in this paper,The experiments show shat our method is practical ,and fits the path-wise automatic generation of test data for both whicte -bos testing and black-blx testing.     

谱聚类算法研究及其在图像分割中的应用

提出了一种改进谱聚类的算法。首先介绍了谱聚类和基于路径的思想;然后为了改善传统谱聚类算法对GAUSS函数中尺度参数的敏感性,提出了一种新算法,并将其扩展到半监督的情况;最后将其应用在图像分割实验中,证明了该算法的有效性。     

遗传算法生成变异测试用例

实际测试用例一般不能满足变异测试充分,但遗传算法搜索空间较大,可使用其生成变异测试充分度较高的测试用例集.适应值函数的构造使用分支函数插装法.首先根据杀死弱变异体的必要性条件,构造必要性条件分支函数,插装于源程序中;然后根据可达性条件,构造可达性条件的分支函数并插装.使用基于面向路径的遗传算法来搜索杀死弱变异体的测试用例.将终止条件改为程序最终结果的不同,插装函数不变,生成满足条件的强变异测试用例.对于多重弱变异,按熙可达路径实施等价类划分,每一个等价类采用与单重弱变异相同的方法.实验结果表明,遗传算法可生成杀死各类变异体的测试用例,优于随机生成的测试用例.     

基于最小聚类单元的聚类算法研究及其在CRM中的应用

将聚类分析技术应用于客户关系管理可以改善客户关系，对将来的趋势和行为进行预测，优化营销策略。在综合分析网格聚类算法和K-均值聚类算法的基础上，提出了基于最小聚类单元（Minimum Clustering Cell，简称MCC）的聚类算法，介绍了该算法在CRM中的应用。经证明该算法是一种实用的、速度更快、效率更高的改进聚类算法，它克服了K-均值聚类需要事先给定K值、网格聚类要求数据密集的缺点。     

Assessing and generating test sets in terms of behavioural adequacy

Identifying a finite test set that adequately captures the essential behaviour of a program such that all faults are identified is a well‐established problem. This is traditionally addressed with syntactic adequacy metrics (e.g. branch coverage), but these can be impractical and may be misleading even if they are satisfied. One intuitive notion of adequacy, which has been discussed in theoretical terms over the past three decades, is the idea of behavioural coverage: If it is possible to infer an accurate model of a system from its test executions, then the test set can be deemed to be adequate. Despite its intuitive basis, it has remained almost entirely in the theoretical domain because inferred models have been expected to be exact (generally an infeasible task) and have not allowed for any pragmatic interim measures of adequacy to guide test set generation. This paper presents a practical approach to incorporate behavioural coverage. Our BESTEST approach (1) enables the use of machine learning algorithms to augment standard syntactic testing approaches and (2) shows how search‐based testing techniques can be applied to generate test sets with respect to this criterion. An empirical study on a selection of Java units demonstrates that test sets with higher behavioural coverage significantly outperform current baseline test criteria in terms of detected faults. © 2015 The Authors. Software Testing, Verification and Reliability published by John Wiley & Sons, Ltd.     

基于模糊聚类分析的教师授课质量评价

用模糊聚类方法对教师授课效果进行分类分析,选取适当的相似系数,建立模糊矩阵,用动态聚类法进行分类分析,其结果不在是传统意义上的名次排序,而是较好地实现了量化评价与综合评价相结合,提高了评价水平,为今后确定评价指标提供了可靠的依据。     

基于模糊聚类分析的教师评价模型

教师教学评价在整个教育系统中发挥着重要作用,对教师做出正确、全面的评价,能够充分调动教师的教学积极性．文中采用模糊聚类方法对教师授课效果进行分类分析,选取适当的相似系数,建立模糊矩阵,用动态聚类法进行分析解释,较好地实现了量化评价与综合评价相结合,从而客观公正地反映教师教学情况．     

Multivariate Time Series Clustering and its Application in Industrial Systems

Abstract

Multivariate Time Series (MTS) data obtained from large scale systems carry resourceful information about the internal system status. Multivariate Time Series Clustering is one of the exploratory methods that can enable one to discover the different types of behavior that is manifested in different working periods of a system. This knowledge can then be used for tasks such as anomaly detection or system maintenance. In this study, we make use of the statistical method, Variable Order Markov Models (VOMMs) to model each individual MTS and employ a new metric to calculate the distances between those VOMMs. The pairwise distances are then used to accomplish the MTS Clustering task. Two other MTS Clustering methods are presented and the superiority of the proposed method is confirmed with the experiments on two data sets from Cyber-Physical Systems. The computational complexity of the presented methods is also discussed.     

灰色聚类法在湿地水体富营养化评价中的应用

将灰色聚类法应用到湿地水体富营养化评价中，旨在建立起一套比较完善、适合于湿地水体富营养化的评价体系。把湿地水体富营养化程度划分为6个级别，其阚值参照中国湖泊富营养化评价标准和湿地富营养化的特点。利用灰类白化权函数描述水体富营养化分级界限，正确地选择了各参评指标对于各等级的聚类权，在此基础上构建了湿地水体富营养化灰色聚类法综合评判模型。并以扎龙湿地为例进行了实例计算与分析，验证了此模型的准确性、可比性和实用性。     

改进的量子遗传算法及其在测试数据生成中的应用

针对测试数据自动生成中收敛速度不够快的缺点,提出一种改进的量子遗传算法(IQGA),其对量子遗传算法的主要改进是：1)在个体更新时,对个体的某一位取反,将取反后的个体用于指导下一代个体的进化;2)对测量后的二进制个体进行变异,而不是传统的互换量子比特的概率幅。将IQGA用于测试数据生成,通过对三个基础程序进行实验,结果表明IQGA在覆盖率和迭代次数两个方面都优于传统量子遗传算法。IQGA不仅能保证种群朝着正确的方向进化,同时有效地避免了早熟现象,能以更快的速度搜索到目标解。     

一种利用确定性退火技术的聚类模型与算法研究

针对传统聚类模型的缺陷,文章利用确定性退火技术,提出一种聚类模型及聚类算法.该模型考虑了聚类的交互作用,以前提出的一些聚类模型是它的特例.引入温度参数,把聚类问题看成一个物理系统,把求解聚类问题的最优解转化为模拟随温度变化的物理系统的平衡态.通过求解一系列随温度变化的物理系统的自由能函数的局部极小来模拟物理系统的平衡态,最终达到物理系统的基态,即聚类问题的最优解.     

一种新的轨迹聚类及有效性评价方法

为解决轨迹聚类问题,提出一种新的无监督轨迹聚类及聚类有效性评估方法。通过建立双层字符串轨迹模型,计算得到轨迹间距离并用作聚类依据。提出轨迹同距点比例的概念,以此作为聚类工具,并采用类内平均同距点比例作为聚类有效性评价值。利用麻省理工大学(Massachusetts Institute of Technology,MIT)停车场行人路径数据集进行实验,实验结果表明,新的无监督聚类算法能较好地完成轨迹聚类任务,平均类内同距点比例能够很好地衡量分类效果。