A fuzzy comprehensive evaluation algorithm for analyzing electronic word-of-mouth

This study evaluates tourism experiences shared through electronic word-of-mouth (eWOM) across four Chinese attractions. The objective is to develop a framework for evaluating eWOM by constructing an indicator system and implementing an analytic hierarchy process with the use of a fuzzy comprehensive evaluation algorithm. This framework is achieved by mapping more than 6000 websites related to Chinese tourism attractions and filtering over 200,000 useful reviews to measure service performance. Results indicate that ecological–biological attractions failed to make tourists feel “very satisfied” in various aspects, such as overall evaluation, infrastructure, traffic, natural environment, and social environment. Overall, the study contributes by presenting a framework that can be adopted by tourism researchers and industry practitioners to understand tourist preferences and evaluate service performance to improve service quality.     

Multivariate Cox Hidden Markov models with an application to operational risk

ABSTRACT

Modeling multivariate time-series aggregate losses is an important actuarial topic that is very challenging due to the fact that losses can be serially dependent with heterogeneous dependence structures across loss types and business lines. In this paper, we investigate a flexible class of multivariate Cox Hidden Markov Models for the joint arrival process of loss events. Some of the nice properties possessed by this class of models, such as closed-form expressions, thinning properties and model versatility are discussed in details. We provide the expectation-maximization (EM) algorithm for efficient model calibration. Applying the proposed model to an operational risk dataset, we demonstrate that the model offers sufficient flexibility to capture most characteristics of the observed loss frequencies. By modeling the log-transformed loss severities through mixture of Erlang distributions, we can model the aggregate losses. Finally, out-of-sample testing shows that the proposed model is adequate to predict short-term future operational risk losses.     

Self-employment of immigrants and natives in Sweden – a multilevel analysis

Recent research suggests that self-employment among immigrants is due to a combination of multiple situational, cultural and institutional factors, all acting together. Using multilevel regression and unique data on the entire population of Sweden for the year 2007, this study attempts to quantify the relative importance for the self-employed of embeddedness in ethnic contexts (country of birth) and regional business and public regulatory frameworks (labour market areas). This information indicates whether the layers under consideration are valid constructs of the surroundings that influence individual self-employment. The results show that 10% (women) and 8% (men) of the total variation in individual differences in self-employment can be attributed to the country of birth. When labour market areas are included in the analyses, the share of the total variation increases to 14% for women and 12% for men. The results show that the ethnic context and the economic environment play a minor role in understanding individual differences in self-employment levels. The results can have important implications when planning interventions or other actions focusing on self-employment as public measures to promote self-employment often are based on geographic areas and ethnic contexts.     

公开密钥算法RSA策略及程序实现

随着通信的飞速发展，信息安全显得越来越重要，计算机密码体制的基本思想就是将要保护的信息变成伪装信息，在公开密钥算法提出之前，所有密码系统的解密密钥和加密密钥彼此有着直接的联系，这也是秘密密钥的缺陷所在。为此公开密钥算法RSA算法就顺应而生。这种叫加密算法可用VB程序编程实现。     

基于无交叉遗传算法的物流车辆路径问题研究

设计并实现了一种求解基本车辆路径问题的无交叉遗传算法,阐述了无交叉遗传算法求解物流车辆路径问题的关键技术,包括编码方案、初始种群生成方案、适应度函数、种群选择方案和变异操作等;并对比了使用目标函数倒数法和目标函数做差法构造适应度函数时的求解效果。实验结果表明,给出的无交叉遗传算法在求解车辆路径问题上具有良好的性能。     

Stock Returns,Productivity, and Corruption in Eight European Fast-Emerging Markets

This article addresses the impact of productivity, corruption, and trade openness on the stock returns of 265 industrial companies listed in eight Eastern European fast-emerging markets, over the 2004-2013 period. Through a three-factor model that includes both measures at firm level and macro-level control variables, our findings suggest that country corruption index is negatively correlated with the total annual return of the stocks of the listed industrial companies of our sample. Moreover, the most productive firms are featured by higher stock returns, while leverage seems not to be a key predictor of stock returns. In addition, the article uncovers innovative evidence about trade openness that is negatively correlated with stock returns due to its connection with the recent financial crisis. That is, firms operating in markets that are more open to trade show a higher degree of interconnection with other economies and are more likely to undergo the effects of negative fluctuations from foreign markets during the economic crisis. © 2015 Wiley Periodicals, Inc.     

A monotonically converging algorithm for the severity of ruin in a discrete semi-markov risk model

This paper deals with the severity of ruin in a discrete semi-Markov risk model. It is shown that the work of Reinhard and Snoussi (Stochastic Models, 18) can be extended to cover the case where the premium is an integer value and no restriction on the annual result is imposed. In particular, it is shown that the severity of ruin without initial surplus is solution of a system of equations. It can be obtained by a monotonically converging algorithm when the claims are bounded.     

A hybrid parallel genetic algorithm for yard crane scheduling

This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-complete problem regarding the yard crane scheduling, a hybrid algorithm, which employs heuristic rules and parallel genetic algorithm (PGA), is then employed. Then a simulation model is developed for evaluating this approach. Finally, numerical experiments on a specific container terminal yard are used for system illustration. Computational results suggest that the proposed method is able to solve the problem efficiently.     

基于改进的BP-LM在中国人口老龄化预测中的应用

由于人口老龄化率的预测具有高度非线性特征，这与BP神经网络能够处理非线性问题的特征相符合，但BP神经网络算法易使解陷入局部极小。基于L-M算法的改进BP神经网络可以有效克服这一问题，而且收敛速度快。通过具体的仿真及实践结果验证了改进BP的有效性，并对未来五年的中国老龄化率进行了预测。     

岩土边坡稳定性的遗传算法分析

非线性优化方法主要缺陷在于当边坡土层为非均质复杂条件时,无法保证搜索到安全系数的全局最小解,而只能搜索到局部极小解。基于遗传算法,建立了搜索岩土边坡稳定性分析最小安全系数和滑移面中心坐标与半径的数值方法。问题的可行解在变量搜索区间内搜索,包括滑弧的圆心坐标和半径。数值模拟结果表明,遗传算法搜索到的边坡稳定最小安全系数与理论解是一致的。