基于深度信念网络的列车故障音频诊断方法

铁路在交通运输行业有着举足轻重的地位，一旦列车发生故障将会导致严重的生命财产损失。由于列车发生故障的概率相对较低，因此难以捕获列车的故障样本。针对上述问题，提出了一种无监督学习的列车故障识别方法，通过检测列车音频信号来识别列车故障。该方法基于深度信念网络(DBN)，利用小波包分解提取检测信号的特征向量并将其作为DBN的输入，待网络充分训练后，由训练好的DBN识别当前列车的运行状况。现场监测实验结果表明，该方法能够在无监督的条件下有效识别列车故障，保障了列车的运行安全。     

我国建筑石油沥青标准的沿革及现状

论述了我国建筑沥青标准的变化历程及现状,对我国建筑沥青的生产、产品质量情况及现行国家标准GB/T 494-1998《建筑石油沥青》的不足之处进行了分析。提出了今后应生产的建筑沥青品种及应参照美国材料与试验协会标准ASTM D312《屋顶用沥青的标准规格》、我国石化行业标准SH/T0002-1990(1998)《防水防潮石油沥青》,修订GB/T494- 1998的建议。以进一步达到增加建筑沥青牌号,提高建筑沥青质量和使用性能的目的,满足建筑工业的发展对沥青多牌号、高质量、使用性能好的要求。     

Revising deductive knowledge and stereotypical knowledge in a student model

A user/student model must be revised when new information about the user/student is obtained. But a sophisticated user/student model is a complex structure that contains different types of knowledge. Different techniques may be needed for revising different types of knowledge. This paper presents a student model maintenance system (SMMS) which deals with revision of two important types of knowledge in student models: deductive knowledge and stereotypical knowledge. In the SMMS, deductive knowledge is represented by justified beliefs. Its revision is accomplished by a combination of techniques involving reason maintenance and formal diagnosis. Stereotypical knowledge is represented in the Default Package Network (DPN). The DPN is a knowledge partitioning hierarchy in which each node contains concepts in a sub-domain. Revision of stereotypical knowledge is realized by propagating new information through the DPN to change default packages (stereotypes) of the nodes in the DPN. A revision of deductive knowledge may trigger a revision of stereotypical knowledge, which results in a desirable student model in which the two types of knowledge exist harmoniously.     

Revising threshold functions

A revision algorithm is a learning algorithm that identifies the target concept, starting from an initial concept. Such an algorithm is considered efficient if its complexity (in terms of the resource one is interested in) is polynomial in the syntactic distance between the initial and the target concept, but only polylogarithmic in the number of variables in the universe. We give an efficient revision algorithm in the model of learning with equivalence and membership queries for threshold functions, and some negative results showing, for instance, that threshold functions cannot be revised efficiently from either type of query alone. The algorithms work in a general revision model where both deletion and addition type revision operators are allowed.     

Uncertainty,belief, and probability1

We introduce a new probabilistic approach to dealing with uncertainty, based on the observation that probability theory does not require that every event be assigned a probability. For a nonmeasurable event (one to which we do not assign a probability), we can talk about only the inner measure and outer measure of the event. In addition to removing the requirement that every event be assigned a probability, our approach circumvents other criticisms of probability-based approaches to uncertainty. For example, the measure of belief in an event turns out to be represented by an interval (defined by the inner and outer measures), rather than by a single number. Further, this approach allows us to assign a belief (inner measure) to an event E without committing to a belief about its negation -E (since the inner measure of an event plus the inner measure of its negation is not necessarily one). Interestingly enough, inner measures induced by probability measures turn out to correspond in a precise sense to Dempster-Shafer belief functions. Hence, in addition to providing promising new conceptual tools for dealing with uncertainty, our approach shows that a key part of the important Dempster-Shafer theory of evidence is firmly rooted in classical probability theory. Cet article présente une nouvelle approche probabiliste en ce qui concerne le traitement de l'incertitude; celle-ci est basée sur l'observation que la théorie des probabilityés n'exige pas qu'une probabilityé soit assignée à chaque événement. Dans le cas d'un événement non mesurable (un événement pour lequel on n'assigne aucune probabilityé), nous ne pouvons discuter que de la mesure intérieure et de la mesure extérieure de l'évenément. En plus d'éliminer la nécessité d'assigner une probabilityéà l'événement, cette nouvelle approche apporte une réponse aux autres critiques des approches à l'incertitude basées sur des probabilityés. Par exemple, la mesure de croyance dans un événement est représentée par un intervalle (défini par la mesure intérieure et extérieure) plutǒt que par un nombre unique. De plus, cette approche nous permet d'assigner une croyance (mesure intérieure) à un événement E sans se compromettre vers une croyance à propos de sa négation -E (puisque la mesure intérieure d'un événement et la mesure intérieure de sa négation ne sont pas nécessairement une seule et unique mesure). II est intéressant de noter que les mesures intérieures qui résultent des mesures de probabilityé correspondent d'une manière précise aux fonctions de croyance de Dempster-Shafer. En plus de constituer un nouvel outil conceptuel prometteur dans le traitement de l'incertitude, cette approche démontre qu'une partie importante de la théorie de l'évidence de Dempster-Shafer est fermement ancrée dans la theorie classique des probabilityés.     

The Design of Discrimination Experiments

Experimentation plays a fundamental role in scientific discovery. Scientists experiment to gather data, investigate phenomena, measure quantities, and test theories. In this article, we address the problem of designing experiments to discriminate between two completing theories. Given an initial situation for which the two theories make the same prediction, the experiment design problem is to determine how to modify the situation such that the two theories make different predictions for the modified situation. The modified situation is called a discrimination experiment. We present a knowledge-intensive method called DEED for designing discrimination experiments. The method analyzes the differences in the two theories' explanations of the prediction for the initial situation. Based on this analysis, it determines modifications to the initial situation that will result in a discrimination experiment. We illustrate the method with the design of experiments to discriminate between several pairs of qualitative theories in the fluids domain.     

守望太阳——论诗集《太阳之歌》

运用马克思主义历史———美学批评方法 ,结合多种批评理论 ,对《太阳之歌》诗集进行全面、系统、多角度的读解 ,肯定了它的艺术成就 ,指出它是现实主义的绚丽花朵     

《石油沥青纸胎油毡》国家标准的修订

《石油沥青纸胎油毡》国家标准进行了第三次修订。本文介绍了修订的理由、修订的内容与依据，并与国内外同类产品标准进行了比较。     

以需求和发展的观点看职教以顽强和创新的精神办职教

职业教育自古有之，且随时代不断发展，其与社会的结合直接而紧密，要切合“业”之所“需”，开拓进取不断创新，提高质量，突出特色，在推动社会进步、经济发展的同时，增强自身的生命力，步人良性循环轨道。     

基于模型修正技术的模拟集成电路几何规划优化方法

为了兼顾模拟集成电路设计优化的求解精度和计算效率,提出一种基于正项式模型修正技术的几何规划优化方法.首先将模拟集成电路的设计目标与约束简化为正项式模型,然后在采用几何规划方法迭代优化的过程中利用晶体管级SPICE仿真不断修正这一正项式模型.实例表明,与传统基于公式的优化方法和基于仿真的优化方法相比,该方法能够在尽量保证计算效率和全局最优解的前提下使优化精度满足晶体管级SPICE仿真的要求.