A new financial stress index model based on support vector regression and control chart

Financial stress index (FSI) is considered to be an important risk management tool to quantify financial vulnerabilities. This paper proposes a new framework based on a hybrid classifier model that integrates rough set theory (RST), FSI, support vector regression (SVR) and a control chart to identify stressed periods. First, the RST method is applied to select variables. The outputs are used as input data for FSI–SVR computation. Empirical analysis is conducted based on monthly FSI of the Federal Reserve Bank of Saint Louis from January 1992 to June 2011. A comparison study is performed between FSI based on the principal component analysis and FSI–SVR. A control chart based on FSI–SVR and extreme value theory is proposed to identify the extremely stressed periods. Our approach identified different stressed periods including internet bubble, subprime crisis and actual financial stress episodes, along with the calmest periods, agreeing with those given by Federal Reserve System reports.     

模糊集的无穷扩展原理

从普通集族{Xt}t?T（T为无限集）的直积Ⅱt?TXt出发，给出模糊集族At?F(Xt)(t?T)的直积概念；将通常的映射?：Ⅱt?TXt→Y扩展为模糊集族的直积Ⅱt?TF(Xt)到Y上的模糊集F(Y)的映射。     

On the difficulty of making social choices

The difficulty of making social choices seems to take on two forms: one that is related to both preferences and the method used in aggregating them and one which is related to the preferences only. In the former type the difficulty has to do with the discrepancies of outcomes resulting from various preference aggregation methods and the computation of winners in elections. Some approaches and results which take their motivation from the computability theory are discussed. The latter institution-free type of difficulty pertains to solution theory of the voting games. We discuss the relationships between various solution concepts, e.g. uncovered set, Banks set, Copeland winners. Finally rough sets are utilized in an effort to measure the difficulty of making social choices.     

军机备件需求量修正的粗糙集方法

本文针对不可量化因素对军机备件需求量的影响,提出了基于粗糙集的备件需求量的修正方法。考虑不可量化因素存在多值性的问题,将不可分辨关系下的经典粗糙集方法拓展成相容关系下的扩展粗糙集方法,通过相容关系下的近似空间获取决策规则,再由决策规则得到修正系数。最后以轮胎类器材为例,说明了修正系数的获取过程。     

Mixed integer (0–1) fractional programming for decision support in paper production industry

This paper presents an effective and efficient method for solving a special class of mixed integer fractional programming (FP) problems. We take a classical reformulation approach for continuous FP as a starting point and extend it for solving a more general class of mixed integer (0–1) fractional programming problems.To stress the practical relevance of the research we focus on a real-life application in paper production industry. The constantly advancing physical knowledge of large scale pulp and paper production did have a substantial impact on an existing DSS in which mixed integer (0–1) fractional programming is introduced. We show that the motivation to solve a real-life fractional programming problem can provide the basis for a new approach in a new context that has an added value of its own, even outside the given application area. We describe the main characteristics of the DSS, the necessity to develop a non-iterative solution procedure and demonstrate both the effectiveness and efficiency of the proposed approach from practical data sets.     

C14. Moments of the kolmogorov-smirnov one-sample statistic

In adaptive estimation, it is often considered that an estimator has made a mistake if the component estimator chosen for use is not the most efficient for the distribution sampled. Theoretical and simulation results point to a fallacy in this line of thought. The Monte Carlo study involves extension of the Princeton Swindle to distributions conditional on a location and scale-free statistic, and to the uniform. The results give a partial explanation for the sometimes surprising robustness of adaptive L-estimators.     

Improving TAIEX forecasting using fuzzy time series with Box–Cox power transformation

Box–Cox together with our newly proposed transformation were implemented in three different real world empirical problems to alleviate noisy and the volatility effect of them. Consequently, a new domain was constructed. Subsequently, universe of discourse for transformed data was established and an approach for calculating effective length of the intervals was then proposed. Considering the steps above, the initial forecasts were performed using frequently used fuzzy time series (FTS) methods on transformed data. Final forecasts were retrieved from initial forecasted values by proper inverse operation. Comparisons of the results demonstrate that the proposed method produced more accurate forecasts compared with existing FTS on original data.     

基于可变精度的加权粗糙集模型在约简中的研究

首先对粗糙集的定义进行了描述,在可变精度的基础上提出了加权粗糙集模型。重新定义了近似空间内的一些概念,给出了加权粗糙集模型的约简概念,指出了加权系数的两种方法。并根据实验分析,得出加权粗糙集模型约简中分类错误增大,约简长度越短,约简所花时间越长等特性。     

基于粗集与AHP的钢铁企业生态经济效果评价

基于钢铁企业的特点和钢铁企业生态经济水平的发展状况,构建生态经济效果评价的初始指标体系;基于粗糙集约简理论对初选指标进行筛选,优化评价体系;基于粗糙集和AHP方法,综合主观定权和客观定权的优势,最终确定钢铁企业生态经济效果评价的权重;然后,对钢铁企业的生态经济效果开展评价,其结果为钢铁产业政策制定提供定量支持。     

基于灰粗集属性知识简约算法的海运规则发现

海运市场运营规则能够帮助海运企业找到盈利增长点,针对海运市场营运规则难于被发现的问题,将灰色系统理论和粗糙集理论进行融合,针对知识约简中分辨函数范式转化过程中的逻辑推演难题,提出了一种基于灰色粗集融合属性的改进约简算法,选取2007年、2010年、2013年、2015年典型年份作为样本年份,应用灰色系统、粗糙集和基于灰粗集知识约简算法分别进行海运市场盈运规则发现实证分析,通过比较证明了该算法的时效性,同时发掘出了当前海运市场的船型、货品、航线、运价、运力间的营运管理规则。