An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.     

Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm

In this paper, we propose a method for improving the accuracy of the estimation of interregional input–output tables, by combining the RAS method and the real-coded Genetic Algorithm (GA); these are simple representative methods for the estimation of an interregional input–output table. By comparing the performance evaluation results obtained using the proposed method, the RAS method, and Simulated Annealing, we verified that the combination of the genetic algorithm and the RAS method can enhance the estimation accuracy of an interregional input–output table. In addition, performance is further enhanced by adjusting GA parameters.     

A Brief Survey of Modern Optimization for Statisticians

Modern computational statistics is turning more and more to high‐dimensional optimization to handle the deluge of big data. Once a model is formulated, its parameters can be estimated by optimization. Because model parsimony is important, models routinely include non‐differentiable penalty terms such as the lasso. This sober reality complicates minimization and maximization. Our broad survey stresses a few important principles in algorithm design. Rather than view these principles in isolation, it is more productive to mix and match them. A few well‐chosen examples illustrate this point. Algorithm derivation is also emphasized, and theory is downplayed, particularly the abstractions of the convex calculus. Thus, our survey should be useful and accessible to a broad audience.     

Tuition fees and social segregation: lessons from a natural experiment at the University of Paris 9-Dauphine

Using a natural experiment, a sharp rise in tuition fees in some of the programmes at the University of Paris 9-Dauphine, we study the impact of tuition fees on students’ pathways, and outcomes. We apply an optimal matching method to the national database of students’ registrations (SISE) to define a typology of pathways. We then use a nonordered multinomial logit model to evaluate the impact of the rise in tuition fees on the types of pathways selected by the university. We show that there is a significant impact on these pathways. The increase in tuition fees reduces geographic and social mobility, thereby accentuating the phenomena of social segregation. Furthermore, contrary to what some of the studies assert, the rise does not appear to encourage greater effort: we find no impact on the graduation success rate.     

An empirical investigation of director selection in movie preproduction: A two-sided matching approach

This paper examines how movie producers recruit directors in the preproduction phase as mutual choices in a two-sided matching model. It conceptualizes that movie attributes and filmmaker characteristics determine the matching outcomes (“who directed which movie”) and in turn indirectly affect movie box office. We exploit a dataset of 4,807 feature films from 1990 to 2010 to examine empirically the complementarities between the movie/producer side and the director side in terms of movie budget, filmmaker track records and social relations. A series of simulations suggest that social relations facilitate positive assortative matching. Further simulation analyses are conducted to quantify the financial implications of movie–director mismatches, as well as the indirect effects of production budget and producer characteristics. The simulation results show that: a) the financial implications of having a mismatched director can be substantial; and b) the indirect effect of production budget and producer characteristics affect movie box office in an interactive manner. These findings can help filmmakers to better understand the financial impacts of movie–director choices and make more informed decisions at the early phase of preproduction.     

提升算法对传统车险索赔频率建模模型的改进——基于我国五省交强险保单数据

广义线性模型作为非寿险定价的经典模型,在非寿险定价中得到了广泛的应用。近年来,以提升算法为代表的机器学习算法在保险领域取得了很好的效果,为保险产品定价提供了一种新的选择。本文将提升算法思想分别融入到回归树模型和广义线性模型(GLM)中去,用得到的新模型对我国车险索赔频率进行预测建模分析,并与传统的回归树模型和GLM进行比较。结果表明,加入提升算法后传统车险索赔频率建模模型的效果得到了很大的改善,并且在不存在过拟合的前提下,随着模型深度和迭代次数的增加,模型的效果也在不断优化。     

使用粒子群算法解决期权定价模型参数校准问题——以heston模型为例

期权定价模型的参数校准问题是一个常见的难题,以heston 模型为例,定价时需要估计6 个参数,参数估计问题实质上是高维非线性规划问题,由于估参函数的性质不好,一般的估参方法常常失效。使用粒子群（PSO）智能算法可以改善该模型的参数校准问题,因为粒子群算法具有内在随机性,因此参数估计中的局部极小值问题可以被较好地解决。使用2017 年12 月20 日的香港恒生指数期权作为估计样本,并对2017 年12 月25 日的期权进行样本外预测,数值结果表明使用heston 模型对期权进行定价并配合粒子群算法估计参数具有良好的定价效果。     

一种基于Edline线特征的车道线识别算法

为了提升车道线检测的准确性和实时性,改良车道偏离预警系统的性能,提出了一种新的车道线识别算法。首先应用投影法对采集到的图像设立感兴趣区域,以此来减少图像中存在的干扰信息;其次应用一种改进后的自适应高斯滤波算法对采集所得图像进行平滑处理,减少图像中不必要的细节;最后采用边缘绘制算法进行边缘检测,在此基础上,提出一种线段检测算法——Edline算法提取边缘线,对检测到的直线段进行筛选和聚类。利用引用计数法对车道线进行跟踪和预测。结果表明,新算法的平均处理时间为17.1 ms,准确率为96.19%,将其应用在车道偏离预警系统中可以有效地提高预警效率,提升预警的准确性和响应速度。研究结果丰富了车道线识别理论,可为车道偏离预警系统的应用及基础研究提供参考。     

On Minimally-supported <Emphasis Type="Italic">D</Emphasis>-optimal Designs for Polynomial Regression with Log-concave Weight Function

This paper studies minimally-supported D-optimal designs for polynomial regression model with logarithmically concave (log-concave) weight functions. Many commonly used weight functions in the design literature are log-concave. For example, and exp(−x ²) in Theorem 2.3.2 of Fedorov (Theory of optimal experiments, 1972) are all log-concave. We show that the determinant of information matrix of minimally-supported design is a log-concave function of ordered support points and the D-optimal design is unique. Therefore, the numerically D-optimal designs can be constructed efficiently by cyclic exchange algorithm.     

Can Federal Grants Mitigate Social Competition?

The European economic integration leads to increasing mobilityof factors, thereby threatening the stability of social transferprograms. This article investigates the possibility to achieveby means of voluntary matching grants both the optimal allocationof factors and the optimal level of redistribution in the presenceof factor mobility. We use a fiscal competition model a la Wildasin(1991) in which states differ in their technologies and preferencesfor redistribution. We first investigate a simple process inwhich the federal authority progressively raises the matchinggrants to the district choosing the lowest transfer and alldistricts respond optimally to the resulting change in transfersall around. This process is shown to increase efficiency ofboth production and redistribution. However, it does not guaranteethat all districts gain, nor that an efficient level of redistributionis attained. Assuming complete information among districts,we derive the willingness of each district to match the contributionof other districts and we show that the aggregate willingnessto pay for matching rates converges to zero when both the efficientlevel of redistribution and the efficient allocation of factorsare achieved. We then describe an adjustment process for thematching rates that will lead districts to the efficient outcomeand guarantee that everyone will gain. (JEL Classification:H23, H70)