基于最近相关性分类器的单样本掌纹识别

为了解决单样本掌纹识别的困难,研究了基于最近相关性分类器(NCC)的单样本掌纹识别方法。首先对掌纹图像进行分块,划分为若干个子图像;然后运用统计特征、傅里叶变换、离散余弦变换(DCT)和Gabor变换4种方法对子图像进行特征提取,将所有子图像的特征向量组合在一起形成该图像的特征向量;最后应用NCC进行分类识别。运用PolyU掌纹图像库,对本文算法进行测试。实验结果表明:与最近邻分类器(NNC)和支持向量机(SVM)相比,在不同大小的子图像上,运用不同的特征提取算法,NCC均提高了识别率;分类时间在0.3～0.7s之间,满足实时系统的需求。     

杭州老虎洞窑古陶瓷成分的化学计量学研究

用支持向量机算法研究了与杭州老虎洞古陶瓷有关的两个断源、断代问题。作为化学计量学的～种新型分类算法,支持向量机在小样本问题上表现出良好的泛化能力,与特征选择方法结合,可以有效处理样本少,特征多的问题。本研究综合利用支持向量机、特征选择算法和其它化学计量学算法研究了杭州凤凰山麓万松岭附近的古窑遗址和“传世哥窑”的断源、断代问题,证明老虎洞窑与郊坛下窑产品截然不同,万松岭附近地面收集瓷片样本是老虎洞窑宋代地层的瓷片滑落所致,而“传世哥窑”样品可能是老虎洞窑元代时的产品。实验表明：支持向量机算法与化学分析相结合可以成为研究古陶瓷断源和断代问题的一种新方法。     

TETRA通信与干扰信号智能识别技术

陆上集群无线电(Terrestrial Trunked Radio,TETRA)数字集群通信系统因其开放性易受到内外部电磁干扰。干扰信号的类型多种多样,针对不同的干扰样式,采取的抗干扰措施也各不相同,因此干扰信号的识别具有重大意义。基于此,提出了一种干扰信号智能识别技术。该技术首先对受到不同干扰后的TETRA音频数据进行特征提取,并筛选出具有分类能力的特征,其次使用决策树、支持向量机和随机森林3种分类模型对特征提取后的待测试信号进行智能分类识别。实验结果表明,使用的这3种模型能够有效判断TETRA系统中的信号是否受到干扰,以及受到何种样式的干扰,可为后续TETRA系统中的信号干扰识别提供参考。     

缆机起重作业驾驶员的操作行为可靠性研究

缆机是大坝浇筑过程中的主要运输设备之一,缆机驾驶员操作水平直接关系缆机起重作业安全.为有效提高缆机起重作业驾驶员操作行为可靠性,预防起重作业安全事故,针对缆机起重作业周期性多维运动的特点,分解驾驶员操作流程;剖析操作行为失误,建立驾驶员行为模式;从时间角度量化操作流程,计算缆机驾驶员操作行为响应失误概率;构建操作行为可靠性分析模型,定量表达操作行为可靠性,分析人因失误对缆机起重作业安全事故的影响.结果表明,吊具与吊罐对接、混凝土卸料等作业过程的缆机驾驶员操作行为可靠性低,需加强安全培训,严格考核制度,从根本上提高缆机驾驶员操作行为的可靠性,以期提升缆机生产效率,实现预防安全事故的目标.     

基于支持向量机的凝血功能诊断模型

使用凝血四项指标诊断凝血功能是临床的常规检查,但根据经验进行诊断正确率不高.剔除临床上最重要的指标FIB后,建立支持向量机模型诊断的正确率和根据凝血四项指标诊断的正确率没有显著差异,100次模拟的平均正确率分别达到了95.4496%和95.5039%.     

The application of automated reasoning to formal models of combinatorial optimization

Many formalisms have been proposed over the years to capture combinatorial optimization algorithms such as dynamic programming, branch and bound, and greedy. In 1989 Helman [9] presented a common formalism that captures dynamic programming and branch and bound type algorithms. The formalism was later extended to include greedy algorithms. In this paper, we describe the application of automated reasoning techniques to the domain of our model, in particular considering some representational issues and demonstrating that proofs about the model can be obtained by an automated reasoning program. The long-term objective of this research is to develop a methodology for using automated reasoning to establish new results within the theory, including the derivation of new lower bounds and the discovery (and verification) of new combinatorial search strategies.     

Choiceless polynomial time

Turing machines define polynomial time (PTime) on strings but cannot deal with structures like graphs directly, and there is no known, easily computable string encoding of isomorphism classes of structures. Is there a computation model whose machines do not distinguish between isomorphic structures and compute exactly PTime properties? This question can be recast as follows: Does there exist a logic that captures polynomial time (without presuming the presence of a linear order)? Earlier, one of us conjectured a negative answer. The problem motivated a quest for stronger and stronger PTime logics. All these logics avoid arbitrary choice. Here we attempt to capture the choiceless fragment of PTime. Our computation model is a version of abstract state machines (formerly called evolving algebras). The idea is to replace arbitrary choice with parallel execution. The resulting logic expresses all properties expressible in any other PTime logic in the literature. A more difficult theorem shows that the logic does not capture all of PTime.     

Cut generation for an integrated employee timetabling and production scheduling problem

This paper investigates the integration of the employee timetabling and production scheduling problems. At the first level, we manage a classical employee timetabling problem. At the second level, we aim at supplying a feasible production schedule for a set of interruptible tasks with qualification requirements and time-windows. Instead of hierarchically solving these two problems as in the current practice, we try here to integrate them and propose two exact methods to solve the resulting problem. The former is based on a Benders decomposition while the latter relies on a specific decomposition and a cut generation process. The relevance of these different approaches is discussed here through experimental results.     

Pooling设计在数控机床可靠性方面的应用

利用随机pooling设计的理论和方法,建立了数控机床可靠性筛选的定量分析数学模型,在统计分析观察工作时间段的基础上,可以筛选出可靠性差的数控机床,为数控机床的改进,产品质量的提高,提供理论依据.     

On weighting two criteria with a parameter in combinatorial optimization problems

Two criteria in a combinatorial problem are often combined in a weighted sum objective using a weighting parameter between 0 and 1. For special problem types, e.g., when one of the criteria is a bottleneck value, efficient algorithms are known that solve for a given value of the weighting parameter.