Intuitionistic Fuzzy Ordered Weighted Cosine Similarity Measure

The aim of this paper is to introduce the intuitionistic fuzzy ordered weighted cosine similarity (IFOWCS) measure by using the cosine similarity measure of intuitionistic fuzzy sets and the generalized ordered weighted averaging (GOWA) operator. Some desirable properties and different families of the IFOWCS measure are investigated. The prominent characteristics of the IFOWCS measure are that not only it is a generalization of some widely used similarity measure, but also it can deal with the correlation of different decision matrices or multi-dimensional arrays for intuitionistic fuzzy values. We further generalize the IFOWCS measure and obtain the intuitionistic fuzzy ordered weighted similarity (IFOWS) measure. In the end, the IFOWS measure with existing similarity measures are compared with the IFOWCS measure by an illustrative example.     

Developing Group Ordered Weighted Averaging Operator Weights for Group Decision Support

A few single decision-making methods under uncertainty (SDMUU) are available in the literature. The reason for such scarcity seems to be mainly due to too insufficient information to induce a reasonable result for effective decision support. Moreover their final outcomes on the same SDMUU problem may be different depending on which method is applied. A group decision-making method under uncertainty (GDMUU) extends a SDMUU in a sense that a group of individuals, each expressing different opinions, work together to solve a relevant problem. As in a SDMUU, we find that just a few methods are available to solve a GDMUU problem. In the paper, the ordered weighted averaging (OWA) method, originally devised for use with the SDMUU problem, is considered to deal with a GDMUU problem where individuals of a group express their degree of optimism in terms of attitudinal characters. We first find the extreme points corresponding to the attitudinal character and then solve a quadratic mathematical program which minimizes a squared distance from each extreme point identified. Thus the resulting OWA operator weights for the group are located at the center of the weights-space constructed by attitudinal characters. This idea is further extended to deal with uncertain attitudinal character expressed in the form of interval in situations where it is difficult to reliably obtain a precise attitudinal character due to time pressure and a limited domain knowledge and so on.     

Generalized Ordered Weighted Reference Dependent Utility Aggregation Operators and Their Applications to Group Decision-Making

To quantify the influence of decision makers’ psychological factors on the group decision process, this paper develops a new class of aggregation operators based on reference-dependent utility functions (RUs) in multi-attribute group decision analysis. RUs include S-shaped RU and non-S-shaped RU. Each RU affords a framework where the psychological factors explicitly enter the decision problem via the basic utility function, reference point and loss aversion coefficient. Under the general framework, we derive a generalized ordered weighted S-shaped RU proportional averaging (GOSP) operator and a generalized ordered weighted non-S-shaped RU proportional averaging (GONSP) operator, respectively. The GOSP operator implies the risk attitude of the DM for relative losses is risk-seeking, while GONSP operator indicates the risk attitude in this case is risk-averse. As a special case, GONSP operator can degenerate into GOWPA operator which means that the attitude of the DM is risk-neutral. Each operator satisfies the desirable properties of general operator, i.e., monotonicity, commutativity, idempotency and boundedness. Furthermore, we consider hyperbolic absolute risk aversion (HARA) function as the basic utility function, and define an S-shaped HARA and a non-S-shaped HARA utility functions. Based on the two new RUs, we propose GOSP–HARA operator and GONSP–HARA operator. Every operator covers many existing aggregation operators. To ascertain weights of such operators, the paper builds an attribute-deviation weight model and a DMs-deviation weight model. Based on these RU operators and weight models, an approach is addressed for solving multiple attribute group decision-making problem. At last, an example is provided to show the feasible of our approach.     

Continuous Ordered Weighted Distance Measure and Its Application to Multiple Attribute Group Decision Making

We develop a new distance measure called the continuous ordered weighted distance (COWD) measure by using the continuous ordered weighted averaging (COWA) operator in the interval distance. We study some properties and different families of the COWD measure. We further generalize the COWD measure. The prominent characteristics of the COWD measure are that it is not only a generalization of some widely used distance measures and the continuous generalized OWA operator, but also it can deal with interval deviations in aggregation on interval arguments by using a controlled parameter. The desirable characteristics make the COWD measure be suitable to wide range situations, such as decision making, engineering and economics. In the end, we develop the new approach to group decision making in investment selection.     

Disagreement without end?

The Third UN Conference on the Law of the Sea meets in New York from August 21 to September 15, 1978, for the second half of its Seventh Session. At its earlier meetings the Conference had not succeeded in mapping out a new international maritime law. The present article analyses the state of the negotiations and the problems still awaiting solution.     

Disagreement points in trade negotiations

This paper analyzes trade negotiations between two large countries in the framework of an alternating-offer bargaining model with endogenous interim disagreement actions. Despite of the flexibility in disagreement tariff selection, the countries would keep the status quo tariffs in disagreement periods as far as the country which benefits from keeping the status quo tariffs compensates for the other country’s foregone gains from deviating in disagreement actions. Each equilibrium outcome converges to a corresponding Nash bargaining solution whose disagreement point reflects the status quo tariff rates as well as the threat of raising the tariff to the Nash tariff rate.     

一个包含异质信念的GARCH模型

文章利用信息交易量得到投资者异质信念的代理变量,给出一个包含投资者异质信念的GARCH（1,1）模型。该模型的估计结果表明,上海证券市场与纽约证券市场上都存在明显的投资者异质信念现象,且异质信念显著放大了中、美证券市场上的投资风险。     

Disagreement in a Multi‐Asset Market

This paper provides a simple framework to study the effect of disagreement in a multi‐asset market equilibrium by considering two agents who disagree about expected returns, variances, and correlation of returns of two risky assets. When agents' subjective beliefs are characterized by mean preserving spreads of a benchmark homogeneous belief, we show that the effect of the disagreement does not cancel out in general and the effect in a multi‐asset market can be very different from a single asset market. In particular, the market risk premium can increase and the risk‐free rate can decrease significantly even when the market is overoptimistic and overconfident.     

Two Types of Disagreement in Group Discussions of Japanese Undergraduates

In this study we investigated the nature of disagreement, which is a necessary component of a good discussion. We obtained 27 group discussion scenes by Japanese undergraduates that were evaluated by two ways: impression rating and ranking. As a result of factor analysis for the impression rating data, five factors were extracted: activeness, multidirection and unification of discussion, relationships of participants, development and sophistication of discussion, and sincerity of the participants, and each factor scores of each scene was simultaneously calculated. Each scene’s rank score was also calculated by relative comparisons. A significant positive correlation was found between the mean factor and the rank scores except for Factor 3 (relationships of participants). To consider the reason for the difference relating to Factor 3’s score, we scrutinized the discussion process of four scenes of the different patterns of the factor and rank scores. From the analysis of conversations, we suggested that this difference reflected ways of disagreement. By introducing a probative discourse tags for discussion (pDTD), we reasoned that the frequency of disagreement made Factor 3’s score negative and the absence of the second part of adjacency pairs made the rank score worse. The explicit speech and actions of blame such as emotional and aggressive expression, and neglect of treatment for the minor opinion made also the discussion unfair, but we think that these behaviors might erupt from the ground made by the accumulated implicit behaviors such as the absence of the second part. We finally concluded that the criticism type of disagreement increased the rank scores, and its censure type produced lower results, and the proper ways of disagreement in group discussions were discussed.     

Reforming the IMF's Weighted Voting System

This paper surveys various proposals to reform the IMF's quota determination process and voting regime. We first provide some necessary context by describing IMF decision rules, including the methods by which the Fund determines quotas according to countries’ relative positions in the world economy. This section also addresses the arbitrariness of the IMF quota determination process and how IMF decision rules hamper developing country influence within the Fund. Following this, we review several proposals designed to provide developing countries greater voice in IMF decision‐making. We conclude that the problems of developing country representation are not likely to be fixed by either reallocating quotas on the margins of the existing IMF system or by tinkering with the quota‐determination formulas. Rather, more fundamental institutional adjustments will be required.     

一种加权聚类划分决策树算法

针对斜划分决策树算法普遍存在时间效率低、部分算法仅能应用于二分类问题,提出了一种基于加权距离的聚类决策树算法。通过Relief-F算法为预测属性计算权重,并将权重用于树结点中数据的聚类过程,使用分簇结果对结点进行多路划分,得到可直接用于多分类问题的决策树。理论分析和实验结果表明,该算法与经典轴平行决策树相比,拥有更好的泛化能力以及相近的算法时间复杂度,与大部分斜决策树相比,在付出更少计算代价的前提下,获得了近似的正确率以及模型简洁度。     

微处理器中三角函数及反三角函数的计算方法

本文介绍了一种在微处理器中用二进制定点运算和查表相结合的方法简单实现三角函数和反三角函数运算的方法。与浮点运算方法相比，可大大提高微处理器的运算速度。     

Turbo码解码过程中的加权算法

本文通过调整迭代解码过程中系统位接收值的加权系数，提出了一种Turbo码加权迭代解码算法。该算法改变了迭代运算后Turbo码解码器输出软值中系统位接收值信息和它的外部估计信息的比重，使Turbo码无论在低信噪比或是在高信噪比时均具有优良的纠错性能。仿真结果显示，采用Turbo码加权迭代解码算法，不仅能提高Turbo码的收敛速度，而且能进一步降低Turbo码解码时的地板值，使Turbo码的比特误码率在高、低信噪比时都能够得到进一步改善。     

Equally Weighted Strategic Allocation and Balanced Funds in Brazil

This article analyzes equally weighted strategic asset allocation portfolios in Brazil between 2004 and 2016 and shows that their average returns are not always statistically greater than those of balanced funds, with significance changing in sub-periods. Fixed-income portfolios frequently outperform balanced funds, whose active management underperforms their declared benchmark portfolios. Balanced funds underperformed probably because they deviated from their investment policy. Transaction costs and other rebalancing frequencies do not change the conclusions. Robustness tests indicate that this evidence is valid out-of-the-sample. Investors can mimic balanced-fund policy and possibly do better by means of indexing according to this policy.     

有序响应变量随机系数模型及其应用

有序响应变量随机系数模型属于多层线性模型。多层线性模型主要处理具有层次结构(嵌套结构)的数据,即分层数据。在分层数据中,不仅有描述个体特征的变量(第一水平),而且有由个体组成的更高层次的变量(第二水平或第三水平)。在对微观主体行为的计量研究中,也会遇到分层数据,可以应用多层线性模型。微观主体行为的测量通常以分类数据(离散型数据)的形式表现,因此需使用离散型多层线性模型。有序响应变量随机系数模型是离散型多层线性模型的一种特殊形式,应用于响应变量为有序分类数据的情形。本文以医疗消费为例。医疗消费行为是指个体对医疗…     

An Ordered Probit Approach to Predicting the Probability of Inflation/Deflation

This paper provides an ordered probit approach that estimates the probability six months in the future of three distinct scenarios for prices: inflation, deflation, or price stability. The traditional way of forecasting inflation is to predict a single level and/or growth rate of the PCE deflator. However, this approach is not useful for identifying options or risks facing decision-makers, especially in financial markets. Also, point estimates of inflation convey a sense of overconfidence. Our approach is more practical for decision-makers who must hedge their portfolios, but it is also useful for policymakers, investors, and consumers who must attach a probability with each possible scenario of future price trends. Our results indicate that since June 2011 the probability of deflation has been persistently higher than of the other two scenarios. Thus, the recent years’ higher deflation probabilities may offer a justification for the persistence of the Federal Reserve’s highly accommodative monetary policy during 2012–14.     

激励在企业管理中的作用

在激烈的竞争条件下,组织要想生存和发展,就必须最大限度地激励组织中的全体成员,充分挖掘其内在潜力,每个管理者都应该研究激励理论,使激励理论在企业管理中发挥其重要的作用。因此,必须通过形式多样、生动活泼、富有吸引力和卓有成效的激励方法,把员工中蕴藏的各种积极性、主动性和创造性充分挖掘出来,使之转化为巨大能量。     

加权多路径路由在LEO卫星星座组网中的仿真应用

给出一种加权多路径路由算法.采用多路径路由技术, 避免了数据路由与转发对单个路径的依赖,提高了星座网络系统的吞吐率、网络抗毁能力,同时使网络负载得到均衡.借助OPNET仿真平台,对算法在星座组网中的性能进行了仿真,并对仿真结果进行了分析与评定.仿真结果表明,该算法使星座组网的抗毁性能、信道利用率等方面得到了显著提高.     

金融机构适当性义务的法律性质与司法审查——基于裁判分歧的分析与展开

为加强对金融市场投资者的保护,各国金融法制已普遍建立金融机构适当性义务规则。我国在部分金融立法中引入适当性义务,约束金融机构的行为规范也日臻完备。然而,由于我国金融立法尚未全面接纳适当性义务,在司法实践中也出现了金融机构与投资者之间法律关系界定混乱,以至于投资者请求权依据不明;金融机构履行适当性义务的司法审查偏于形式化、金融机构履行风险揭示义务认定难等问题。为了更好地发挥适当性义务的规范功能,应当将金融机构与投资者之间的关系主要界定为金融服务关系,以明确投资者的请求权基础。在判断金融机构履行适当性义务时,应兼顾程序审查和实质审查两个维度,并结合格式合同和说明义务,来认定金融机构是否履行风险揭示义务。     

基于加权支持向量机的金融时间序列预测

金融时间序列数据的预测是商业领域的热点问题,对金融时间序列进行准确的预测,对金融投资决策与风险管理具有特别重要的意义。针对金融时间序列的特点,对传统支持向量机进行了改进,提出了基于加权支持向量机的金融时间序列预测方法。研究表明,与传统金融时间序列预测方法比较,基于加权支持向量机有效地提高了金融时间序列预测的精度。