An Optimal Experimental Design Perspective on Radial Basis Function Regression

This article provides a new look at radial basis function regression that reveals striking similarities with the traditional optimal experimental design framework. We show theoretically and computationally that the so-called relevant vectors derived through the relevance vector machine (RVM) and corresponding to the centers of the radial basis function network, are very similar and often identical to the support points obtained through various optimal experimental design criteria like D-optimality. This allows us to provide a statistical meaning to the relevant centers in the context of radial basis function regression, but also opens the door to a variety of ways of approach optimal experimental design in multivariate settings.     

汉语时体的分类和语义解释

英汉语在时体分类和对时间看法上存在的差异,使英汉语时体分类和语义解释难以一一对应,因而对汉语时体进行语义解释不能直接延用英语的语义解释方式,而必须对汉语时体的语义特性进行分析,并在此基础上使用中间语言形式化地描述语义特性,才能有效地解决汉英机器翻译中的时体处理问题.汉语的"了"、"过"、"在"、"着"、"起来"和"下去",在语义上相对应,是常用的典型时体标记,以它们为例进行语义对比分析,以时态逻辑为形式化描述手段,较好地体现了汉语时体之间的语义差异.     

统一集经济控制机在企业风险管理中的应用

企业经营面临越来越多的风险,通过运用 COSO（Committee of Sponsoring Organizationos of Treadway Commission） 的企业风险管理（Enterprise Risk Management, ERM） 整合框架并结合自身的具体情况,企业可以制定和实施自身的风险管理策略。统一集经济控制机（AllSet Economic Control Machine,AECM）与该框架有一些相似之处,前者可以用于实施ERM的许多方面,可作为ERM执行的信息基础平台;而ERM框架也在某种程度上表明了AECM的应用价值和空间,并对AECM的具体应用有一定指导作用。本文在分析了AECM和ERM两者之间关系基础上,主要从整体上研究如何将AECM运用于企业风险管理,并初步讨论了如何在AECM中引入ERM的思想来提高其风险管理效用。     

液压系统故障对挖掘机性能的影响

随着科技的发展,液压传动在工程机械中应用越来越广泛。液压系统作为液压挖掘机的一个重要组成部分,其系统性能及工作质量直接影响到挖掘机的工作效率和可靠性。本文从主泵调节器、液压缸、驱动泵上的单向阀、管路、液压油等几个方面对挖掘机液压系统故障进行分析,总结其对整台挖掘机的影响,并给出排出故障的方法。     

基于DSP的工业平缝机伺服控制系统

以工业平缝机伺服控制系统为研究对象,基于永磁同步电机数学模型和磁场定向控制原理,提出了一种基于 DSP芯片MC56F8255的伺服控制系统。对系统整体控制方案进行了分析,设计了驱动电路、信号检测电路等,完成了M/T 测速法、积分分离PID控制算法等软件开发。仿真与实验结果表明,该伺服控制系统响应速度快、超调量小、稳态精度高。     

一种卧式双主轴数控钻孔专机的设计

介绍了一种加工Buick轿车无级变速离合器总成中二 /四档HUB零件的卧式双主轴数控钻孔专机的结构 ,回转夹具及气动控制原理 ,用实例说明了多品种零件加工组合机床在生产中的应用。     

机器学习及其相关算法综述

自从计算机被发明以来,人们就想知道它能不能学习。机器学习从本质上是一个多学科的领域。它吸取了人工智能、概率统计、计算复杂性理论、控制论、信息论、哲学、生理学、神经生物学等学科的成果。文章主要从统计学习基础的角度对机器学习的发展历程以及一些相关的常用算法进行了简要的回顾和介绍。     

Confounding adjustment methods for multi-level treatment comparisons under lack of positivity and unknown model specification

Imbalances in covariates between treatment groups are frequent in observational studies and can lead to biased comparisons. Various adjustment methods can be employed to correct these biases in the context of multi-level treatments (> 2). Analytical challenges, such as positivity violations and incorrect model specification due to unknown functional relationships between covariates and treatment or outcome, may affect their ability to yield unbiased results. Such challenges were expected in a comparison of fire-suppression interventions for preventing fire growth. We identified the overlap weights, augmented overlap weights, bias-corrected matching and targeted maximum likelihood as methods with the best potential to address those challenges. A simple variance estimator for the overlap weight estimators that can naturally be combined with machine learning is proposed. In a simulation study, we investigated the performance of these methods as well as those of simpler alternatives. Adjustment methods that included an outcome modeling component performed better than those that focused on the treatment mechanism in our simulations. Additionally, machine learning implementation was observed to efficiently compensate for the unknown model specification for the former methods, but not the latter. Based on these results, we compared the effectiveness of fire-suppression interventions using the augmented overlap weight estimator.     

聚类视角下的差异工件平行机批调度问题

从聚类角度研究差异工件批调度这一组合优化问题.论证了差异工件的分批问题实质为一种广义聚类问题,为求解批调度问题提供了一个全新的途径.提出了批的空间浪费比的概念,将最小化批的总加工时间目标变换为最小化批的加权空间浪费比,从而可以更容易地寻找启发式信息指导分批过程,两者的等价性也在文中给出了证明.此外,以批的空间浪费比为基...     

基于非线性分位数回归模型的多期VaR风险测度

多期VaR主要受到持有期及波动率两个变量的影响,并且其影响模式(线性或非线性)的确定对于准确地进行VaR风险测度至关重要。非线性分位数回归模型,能够克服线性分位数回归模型只能揭示多期VaR及其影响因素之间线性依赖关系的局限,从而提高多期VaR风险测度的准确性。结合波动模型与两个非线性分位数回归方法:QRNN和SVQR,给出了多期VaR风险测度的三类方案:波动模型法、QRNN+波动模型法、SVQR+波动模型法。选取3个股票价格指数作为研究对象,考虑了6种不同形式的波动模型,得到了18个多期VaR风险测度方法进行实证比较,结果表明:波动模型选择影响到多期VaR风险测度效果;SVQR+波动模型法略优于QRNN+波动模型法,并且两者显著优于波动模型法。