Quasi-sure Flows Associated with Vector Fields of Low Regularity

The authors construct a solution Ut（x） associated with a vector field on the Wiener space for all initial values except in a 1-slim set and obtain the 1-quasi-sure flow property where the vector field is a sum of a skew-adjoint operator not necessarily bounded and a nonlinear part with low regularity, namely one-fold differentiability. Besides, the equivalence of capacities under the transformations of the Wiener space induced by the solutions is obtained.     

Multidimensional stability of planar waves for delayed reaction-diffusion equation with nonlocal diffusion

In this paper, we consider the multidimensional stability of planar waves for a class of nonlocal dispersal equation in $n$--dimensional space with time delay. We prove that all noncritical planar waves are exponentially stable in $L^{\infty}(\RR^n )$ in the form of $\ee^{-\mu_{\tau} t}$ for some constant $\mu_{\tau} =\mu(\tau)>0$( $\tau >0$ is the time delay) by using comparison principle and Fourier transform. It is also realized that, the effect of time delay essentially causes the decay rate of the solution slowly down. While, for the critical planar waves, we prove that they are asymptotically stable by establishing some estimates in weighted $L^1(\RR^n)$ space and $H^k(\RR^n) (k \geq [\frac{n+1}{2}])$ space.     

新型三嗪衍生物的摩擦学性能

合成了一系列双烷基胺基单硫磷酸酯基三嗪衍生物,在四球摩擦磨损试验机上研究了它们作为菜籽油添加剂的摩擦学性能。实验结果表明,该类化合物具有良好的极压抗磨性能,是一类可以用于生物降解润滑油的添加剂。用X-射线光电子能谱（XPS）和扫描电子显微镜（SEM）分析了钢球磨损表面,探讨了该类添加剂的摩擦学机理。在摩擦过程中,钢球表面形成了一层起减摩抗磨性能的含硫,磷无机膜和有机氮复合膜。     

组合调整频率会影响投资者的回报率么?——基于分析师股票推荐的投资策略研究

利用巨灵数据库的分析师评级数据,从投资者角度建立动态组合,检验了按每日、每周、每两周、每月、每季度头寸调整频率后的超额收益,研究发现:"买入"评级组合在各种头寸调整频率策略下都获得了超越市场指数的超额回报率,其中按每周频率进行头寸调整策略获得的市场调整后平均超额回报率最高,按三个月频率进行头寸调整策略获得的市场调整后平均超额回报率最低。投资者在面对分析师一致认为"买入"评级股票时,可按照每周更新的频率构建组合,以获取较高的超额回报率。投资者如果按季度调整频率来卖出股票可能会错失投资机会,卖掉的股票很可能会跑赢市场,投资者可按每两周或每四周的频率调整投资组合中的股票,卖出负面推荐评级"减持/卖出"股票,降低投资亏损。     

Some aspects of scatter search in the flow-shop problem

The flow-shop scheduling problem with the makespan criterion is a certain strongly NP-hard case from the domain of OR. This problem, having simple formulation contrasting with its troublesome, complex and time-consuming solution methods, is ideal for testing the quality of advanced combinatorial optimization algorithms. Although many excellent approximate algorithms for the flow-shop problem have been provided, up till now, in the literature, some theoretical and experimental problems associated with an algorithm’s activity still remain unexamined. In this paper, we provide a new view on the solution space and the search process. Relying upon it, we are proposing the new approximate algorithm, which applies some properties of neighborhoods, refers to the big valley phenomenon, uses some elements of the scatter search as well as the path relinking technique. This algorithm shows up to now unprecedented accuracy, obtainable within a short time on a PC, which has been confirmed in a wide variety of computer tests. Good properties of the algorithm remain scalable if the size of instances increases.     

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本文研究了独立随机变量之和的绝对矩的几个性质, 其中包括$\ep|X+Y|-\ep|X-Y|$的表达式, 这里$X$和$Y$是相互独立的随机变量.     

Banach空间上变分不等式的一个超梯度方法

把王宜举等人[Modified extragradient—type method for variational inequali—ties and verification of the existence of solutions,J.Optim.Theory Appl.,2003,119:167-183]在欧氏空间上求解变分不等式的一个超梯度型方法推广到Banach空间.变分不等式中的算子不要求是一致连续的,其主要优点在于不管变分不等式是否有解,算法都是可执行的.此外,变分不等式的可解性可以通过算法产生的序列的性态来刻画.在适当的条件下,算法产生的序列强收敛于变分不等式的一个解,这是Bregman距离意义下离初始点最近的解.本文的主要结果推广和改善了近来文献中的相应结果.     

Estimating the distortion parameter of the proportional hazards premium for heavy-tailed losses under Lévy-stable regime

Estimating the distorted parameter in the case of non negative heavy-tailed losses has been treated in Brahimi et al. (2011). In this paper, we extend this work to the case of the real heavy-tailed losses. We derive an asymptotic distribution of the estimator. We construct a practically implemented confidence interval for the distortion parameter and illustrate the performance of the interval in a simulation study with application to real data.     

A carbon risk prediction model for Chinese heavy-polluting industrial enterprises based on support vector machine

Chinese heavy-polluting industrial enterprises, especially petrochemical or chemical industry, labeled low carbon efficiency and high emission load, are facing the tremendous pressure of emission reduction under the background of global shortage of energy supply and constrain of carbon emission. However, due to the limited amount of theoretic and practical research in this field, problems like lacking prediction indicators or models, and the quantified standard of carbon risk remain unsolved. In this paper, the connotation of carbon risk and an assessment index system for Chinese heavy-polluting industrial enterprises (eg. coal enterprise, petrochemical enterprises, chemical enterprises et al.) based on support vector machine are presented. By using several heavy-polluting industrial enterprises’ related data, SVM model is trained to predict the carbon risk level of a specific enterprise, which allows the enterprise to identify and manage its carbon risks. The result shows that this method can predict enterprise’s carbon risk level in an efficient, accurate way with high practical application and generalization value.