Modelling the dynamics of the students’ academic performance in the German region of the North Rhine-Westphalia: an epidemiological approach with uncertainty

Student academic underachievement is a concern of paramount importance in Europe, where around 15% of the students in the last high school courses do not achieve the minimum knowledge academic requirement. In this paper, we propose a model based on a system of differential equations to study the dynamics of the students’ academic performance in the German region of the North Rhine-Westphalia. This approach is supported by the idea that both good and bad study habits, are a mixture of personal decisions and influence of classmates. This model allows us to forecast the student academic performance by means of confidence intervals over the next few years.     

Automatic learners with feedback queries

Automatic classes are classes of languages for which a finite automaton can decide whether a given element is in a set given by its index. The present work studies the learnability of automatic families by automatic learners which, in each round, output a hypothesis and update a long-term memory, depending on the input datum, via an automatic function. Many variants of automatic learners are investigated: where the long-term memory is restricted to be the current hypothesis whenever this exists, cannot be of length larger than the length of the longest datum seen, or has to consist of a constant number of examples seen so far. Learnability is also studied with respect to queries which reveal information about past data or past computation history; the number of queries per round is bounded by a constant.     

茂金属催化剂及其聚合物的进展

茂金属催化剂是近年出现的新型催化剂，技术进步很快。应用此催化剂生产的聚烯烃产量快速增加，正逐渐挤占非茂金属聚烯烃市场，而国内还没有茂金属聚烯烃的生产，产业前景广阔。推介了国外发展该技术及其产业的一些做法。     

On solutions to fuzzy stochastic differential equations with local martingales

This paper deals with a class of fuzzy stochastic differential equations (FSDEs) driven by a continuous local martingale under the Lipschitzian condition. Such equations can be useful in modeling hybrid systems, where the phenomena are simultaneously subjected to two kinds of uncertainties: randomness and fuzziness. The solutions of the FSDEs are the fuzzy stochastic processes, and their uniqueness is considered to be in a strong sense. Thus, the existence and uniqueness of solutions to the FSDEs under the Lipschitzian condition is first proven. Moreover, some asymptotic properties of the solutions to the FSDEs are investigated. Finally, an illustrating example on the interest term model is provided.     

ON GENERALIZED FRACTIONAL PROCESSES

Abstract. A class of stationary long-memory processes is proposed which is an extension of the fractional autoregressive moving-average (FARMA) model. The FARMA model is limited by the fact that it does not allow data with persistent cyclic (or seasonal) behavior to be considered. Our extension, which includes the FARMA model as a special case, makes use of the properties of the generating function of the Gegenbauer polynomials, and we refer to these models as Gegenbauer autoregressive moving-average (GARMA) models. While the FARMA model has a peak in the spectrum at f = 0, the GARMA process can model long-term periodic behavior for any frequency 0 f 0.5. Properties of the GARMA process are examined and techniques for generation of realizations, model identification and parameter estimation are proposed. The use of the GARMA model is illustrated through simulated examples as well as with classical sunspot data.     

ON THE ROBUST PREDICTION AND INTERPOLATION OF TIME SERIES IN THE PRESENCE OF CORRELATED NOISE

Abstract. We consider the problem of predicting and interpolating linearly a time series which can be represented as the sum of a model process with known spectral density and a noise process. The spectral density of the noise process is unknown with the exception of an upper bound for its integral. Some partial information of quite general kind about the cross spectral density of model and noise is available. We prove the existence of a robust predictor which minimizes the maximal mean-square error, where the maximum is taken over all spectral densities which may arise from the circumstances described above as spectral density of the predicted time series. An analogous result holds for the related interpolation problem. We describe how to derive the minimax robust predictor and interpolator in concrete situations. The method is illustrated by determining the robust predictor explicitly for three examples where model and noise may be arbitrarily, only causally or not at all correlated.     

环氧氯丙烷的生产技术与市场分析

综述了环氧氯丙烷国内外生产现状 ,消费概况及生产技术 ,并对其发展前景作了初步预测     

中长期负荷预测研究与管理一体化应用平台的构建

论文提出了一种构建中长期负荷预测研究与管理一体化应用平台的设想.平台中,建立了经济、能源及电力生产数据的数据库,实现了经济与用电典型样本监测,建立电力与经济预测系统.该平台主要实现中长期负荷预测的相关研究、分析、预测功能,实现对于负荷预测相关工作的全过程管理,共享基础数据资源与预测结论,规范预测流程,统一预测指标体系,能有效提高工作效率与质量.该平台已在国网安徽省电力公司建设实现,并已试运行.     

基于分形理论的短期电力负荷预测*

电力负荷预测是电力系统规划的重要组成部分,也是电力系统经济运行的基础,其对电力系统规划和运行都极其重要。具有精确的预测方法可以保证能源的节约,避免资源的浪费。同时也可以缓解电能短缺所造成的重大影响。论文为了实现更好的电力负荷预测方法,研究了分形理论在电力负荷上的应用。将分形拼贴定理和分形插值法应用到电力负荷预测之中。提出了分形理论电力负荷预测模型,得到了分形插值预测模型。为了证明分形插值法的有效性,论文将分形预测模型与传统的BP神经网络电力负荷预测模型相比较。最后通过仿真算例说明了论文提出的分形插值预测模型预测精度更高,预测相对误差较小。并且分形理论可以很好地应用在电力系统负荷预测中,预测效果要好于BP神经网络预测模型。     

基于隶属函数的骆岗机场新型大雾预报方法

准确预报大雾对机场减少航班大面积延误和旅客滞留有重要意义。本文阐述一种适用于机场的大雾短时预报方法。通过选取骆岗机场历史地面逐时观测气象资料,依据气温趋势不同类型,运用模糊隶属度与发生条件概率模型,分别建立短时大雾的预报方法。利用VC++程序开发了骆岗机场大雾短时预报软件,可扩展硬件构建实时预警系统。使用2011年地面资料检验结果显示:对未来3小时大雾预报准确率为91.3%,TS评分为0.84。因此,本文提出的大雾短时预报方法在骆岗机场附近3小时大雾预报中是有效的。