油气配产问题的多目标规划模型及实证研究

在进行油气配产时,为了得到最优的配产计划,决策者往往需要考虑多个因素、多个目标,然而这些目标有的是不协调的,甚至是相互矛盾的。笔者根据石油企业油气配产的实际,提出了运用多目标规划的方法来解决该问题,建立了总资金投入量最小、总采油成本最低、总产量最大以及总利润最大的"多位一体"的多目标规划模型,并以D油田为例进行了实证研究,据此制订了该油田2010年的多目标配产方案,并与该油田实际的配产方案进行了对比,结果验证了模型的有效性,并指出了下一步研究的方向。     

最优污染水平的数学解析与模式

针对环境经济学中最优污染水平概念模糊的问题，运用几何解析与逻辑推演方法，分析最优污染水平定性模式的病症所在，导出最优污染水平的充分条件和必要条件，并进一步运用导数和微分学理论证明了该充分条件和必要条件的正确性，从而创建了新的最优污染水平的定量模式。     

中国制造业并购目标的财务特征及预测

并购目标的选择关系到并购事件的成败,制造业是中国经济的重要组成部分,也是并购发生最频繁的行业,识别制造业目标公司的财务特征并对其进行预测具有很大的理论及现实意义。以2013年中国A股市场制造业并购目标为研究对象,选取代表企业各方面能力的20个财务变量,通过单因素方差分析将其与股本规模类似的制造业非目标公司和非制造业并购目标进行比较,实证分析结果表明制造业目标公司具有负债水平高、收益水平低、每股获利能力强、现金短缺、股权集中度低等特点。另外,制造业目标公司和非制造业目标公司在财务特征上不存在显著差异。采用多重共线性诊断并构建Logit回归模型以预测制造业并购目标,模型总体准确率为70.4%,表明对制造业并购目标进行预测在很大程度上是可行的。     

Error analysis of finite difference and Markov chain approximations for option pricing

Mijatovi? and Pistorius proposed an efficient Markov chain approximation method for pricing European and barrier options in general one‐dimensional Markovian models. However, sharp convergence rates of this method for realistic financial payoffs, which are nonsmooth, are rarely available. In this paper, we solve this problem for general one‐dimensional diffusion models, which play a fundamental role in financial applications. For such models, the Markov chain approximation method is equivalent to the method of lines using the central difference. Our analysis is based on the spectral representation of the exact solution and the approximate solution. By establishing the convergence rate for the eigenvalues and the eigenfunctions, we obtain sharp convergence rates for the transition density and the price of options with nonsmooth payoffs. In particular, we show that for call‐/put‐type payoffs, convergence is second order, while for digital‐type payoffs, convergence is generally only first order. Furthermore, we provide theoretical justification for two well‐known smoothing techniques that can restore second‐order convergence for digital‐type payoffs and explain oscillations observed in the convergence for options with nonsmooth payoffs. As an extension, we also establish sharp convergence rates for European options for a rich class of Markovian jump models constructed from diffusions via subordination. The theoretical estimates are confirmed using numerical examples.     

认知OFDM系统旁瓣抑制新方法

针对认知正交频分复用（OFDM）系统带外辐射（OBR）严重问题,在研究基于功率谱密度的主动干扰消除算法（PSD-AIC）模型的基础上,提出了动态PSD-AIC的方法,通过对每一子载波位置OBR的计算,比较选择出OBR取值最小处,作为对消子载波的最优位置,显著改善了系统对OBR的抑制性能（增大约10dB）。对比分析了算法的计算开销,研究了设计参数对OBR的影响,提出了实际应用时的参数选择基准。仿真结果和理论分析表明,动态PSD-AIC方法可以显著减小带外干扰。与PSD-AIC方法相比,旁瓣抑制深度可增加约10dB;与传统AIC方法相比,只需相似计算量,干扰抑制性能便可明显增加。     

改革开放以来我国贸易条件的变动分析与预测

随着我国近几年来经济高速增长,产业结构的不断优化升级,在国际贸易问题上也遇到了许多新的问题。本文将以我国近年来我国制成品贸易以及我国商品贸易条件为研究对象,分析现阶段我国制成品贸易受商品贸易条件恶化和收入贸易条件变化改善的影响,同时对未来两年的商品贸易条件和收入贸易条件以及制成品的出口变动情况进行分析与预测。     

减脂、减糖与科学瘦身

科学瘦身不等于不吃,是合理的减掉脂肪和糖类的摄入,同时视个人身体状况循序渐进的增加体育运动,重视运动生热效应,燃烧脂肪,增加能量消耗,还要按照人体生物钟的运行规律优化睡眠,休息好。     

谈高压配网输变电工程可研阶段系统规划设计收资

文章就高压配网输变电工程可研阶段的系统规划设计收资情况作简要的分析,并通过工程实例,罗列出进行系统规划设计前所需要收集的大量数据及收资方法,以供同行参考。     

Cross Validation Calibration Based Shrinkage – Revisited for the Construction of Prognostic Indices

The use of shrinkage methods for the construction of prognostic indices has been paid increasing attention in the literature on medical statistics in the last years. One approach for the construction of a shrinkage factor is cross validation calibration as suggested by van H ouwelingen and le C essie (1990). We investigate this approach in more detail. First we try to clarify why shrinkage factors constructed by cross validation calibration tend to be smaller than 1. Second we explain why use of this shrinkage factor can result in an improvement of the average prediction error. Third we investigate the possible gain for constellations relevant in medical research by means of a simulation study, focusing on the dilemma, that the improvement on average has to be paid by distinct deteriorations for some patients. Finally we conclude that it is necessary to rethink the choice of loss functions in constructing prognostic indices before recommendations about the use of shrinkage methods can be made.     

An investigation of transformation-based prediction interval for the Weibull median life

Statistical inference based on the Weibull distribution, a distribution widely used in reliability and survival analysis, is usually difficult as it often involves numerical computation and approximation. However, this distribution can be transformed to near-normality by a simple power transformation. Based on this transformation, a prediction interval (PI) for its median can be easily constructed through an inverse transformation. The procedure for selecting the best power transformation through minimizing Kullback-Leibler information is described. The property of this transformation-based PI is investigated. Simple correction factors are also proposed. It is shown that the transformation-based PI with corrections performs well, irrespective of the sample size and parameter values. Simulation results show that the new PI generally outperforms the existing PI. Numerical examples are given for illustration.