New results on the robust stability analysis of neural networks with discrete and distributed time delays

Delay-dependent robust stability of cellular neural networks with time-varying discrete and distributed time-varying delays is considered. Based on Lyapunov stability theory and the linear matrix inequality （LMIs） technique, delay-dependent stability criteria are derived in terms of LMIs avoiding bounding certain cross terms, which often leads to conservatism. The effectiveness of the proposed stability criteria and the improvement over the existing results are illustrated in the numerical examples.     

A STAGE-STRUCTURED SI ECO-EPIDEMIOLOGICAL MODEL WITH TIME DELAY AND IMPULSIVE CONTROLLING*

This paper formulates a robust stage-structured SI eco-epidemiological model with periodic constant pulse releasing of infectious pests with pathogens. The authors show that the conditions for global attractivity of the ＇pest-eradication＇ periodic solution and permanence of the system depend on time delay, hence, the authors call it ＂profitless＂. Further, the authors present a pest management strategy in which the pest population is kept under the economic threshold level （ETL） when the pest population is uniformly persistent. By numerical analysis, the authors also show that constant maturation time delay for the susceptible pests and pulse releasing of the infectious pests can bring obvious effects on the dynamics of system.     

动态抗饱和平滑切换控制器设计方法

针对一类受饱和约束的切换系统,提出了一种动态抗饱和平滑切换控制器的设计方法。首先,基于模型依赖平均驻留时间的方法设计了平滑切换控制器,能够确保系统全局一致渐进稳定并具有一定的鲁棒性能。同时,通过引入链式切换律降低控制器设计的保守性。在此基础上,给出动态抗饱和补偿器的设计方法。将动态抗饱和补偿器设计问题转化为受线性矩阵不等式组约束的优化问题。以航天器在轨加注过程姿态控制系统为例,建立了该系统的链式平滑切换模型,上述模型能够更加准确地反映系统转动惯量的渐变特性。最后,数值仿真算例表明了所提出的控制器设计方法的有效性。     

The distributed representation for societal risk classification toward BBS posts

The risk classification of BBS posts is important to the evaluation of societal risk level within a period. Using the posts collected from Tianya forum as the data source, the authors adopted the societal risk indicators from socio psychology, and conduct document-level multiple societal risk classification of BBS posts. To effectively capture the semantics and word order of documents, a shallow neural network as Paragraph Vector is applied to realize the distributed vector representations of the posts in the vector space. Based on the document vectors, the authors apply one classification method KNN to identify the societal risk category of the posts. The experimental results reveal that paragraph vector in document-level societal risk classification achieves much faster training speed and at least 10% improvements of F-measures than Bag-of-Words. Furthermore, the performance of paragraph vector is also superior to edit distance and Lucene-based search method. The present work is the first attempt of combining document embedding method with socio psychology research results to public opinions area.     

Maximum likelihood estimator of the parameter for a continuous one-parameter exponential family under the optimal ranked set sampling

This paper studies a maximum likelihood estimator (MLE) of the parameter for a continuous one-parameter exponential family under ranked set sampling (RSS). The authors first find the optimal RSS according to the character of the family, viz, arrange the RSS based on quasi complete and sufficient statistic of independent and identically distributed (iid) samples. Then under this RSS, some sufficient conditions for the existence and uniqueness of the MLE, which are easily used in practice, are obtained. Using these conditions, the existence and uniqueness of the MLEs of the parameters for some usual distributions in this family are proved. Numerical simulations for these distributions fully support the result from the above two step optimizations of the sampling and the estimation method.     

Some open problems related to creative telescoping

Creative telescoping is the method of choice for obtaining information about definite sums or integrals. It has been intensively studied since the early 1990s, and can now be considered as a classical technique in computer algebra. At the same time, it is still a subject of ongoing research. This paper presents a selection of open problems in this context. The authors would be curious to hear about any substantial progress on any of these problems.     

基于SD-SEM模型的消费者食品安全风险感知的信息搜寻行为

本文利用系统动力学模型和结构方程模型来研究消费者食品安全风险感知和消费者信息搜寻行为之间的关系,在总结消费者食品安全风险感知和消费者食品安全信息搜寻行为研究文献的基础上,利用结构方程确定消费者食品安全风险感知的影响因素及其之间的路径系数,进而建立系统动力学模型模拟信息搜寻行为对消费者食品安全风险感知的影响,以提出降低消费者食品安全风险感知的建议.     

基于网络关注度的大宗商品市场预测研究

随着大宗商品市场化的加快和电子信息技术的快速发展,以互联网为载体的网络信息将方便快捷地传递到市场及市场参与者.本文从海量开源数据出发,利用搜索引擎平台,提取核心信息构建网络关注度指标,并提出了基于网络关注度的大宗商品价格预测模型.通过引入具有不同核函数的支持向量回归模型,分别建立了针对单个市场(原油、铜以及玉米)的网络关注度预测模型和综合考虑市场间联动性的多市场网络关注度预测模型.实证结果表明,网络关注度对于市场价格的变动有显著的格兰杰因果关系,引入网络关注度指标和相关市场信息能显著提高预测精度.     

A DEA-TOPSIS method for multiple criteria decision analysis in emergency management

A hybrid approach of DEA (data envelopment analysis) and TOPSIS (technique for order performance (preference) by similarity to ideal solution) is proposed for multiple criteria decision analysis in emergency management. Two DEA-based optimization models are constructed to facilitate identifying parameter information regarding criterion weights and quantifying qualitative criteria in TOPSIS. An emergency management case study utilizing data from the Emergency Management Australia (EMA) Disasters Database is provided to demonstrate the feasibility of the proposed analysis procedure.