基于ANP-PP-SPA的区域洪灾风险评价模型研究

针对现有洪灾风险评价模型的缺陷与不足,从致灾因子、孕灾因子、承灾因子和减灾因子4个方面,通过对14项评价指标的分析与计算,构建洪灾风险评价体系。洪灾风险评价体系以网络层次分析法(ANP)求解主观权重,投影寻踪法(PP)求解客观权重,主客观综合权重与集对分析理论(SPA)耦合,构建基于ANP-PP-SPA的洪灾风险评价模型。以广东省英德市为例,验证洪灾风险评价模型的适用性。计算结果表明,英德市2016年的洪灾风险属于中等级别,符合英德市2016年的实际情况。洪灾风险评价模型不仅综合考虑了评价指标间的相互关系,还较好地体现了洪灾风险的模糊性和随机性,能够为区域洪灾风险决策和洪水管理提供科学依据。     

Factor extraction using Kalman filter and smoothing: This is not just another survey

Dynamic factor models have been the main “big data” tool used by empirical macroeconomists during the last 30 years. In this context, Kalman filter and smoothing (KFS) procedures can cope with missing data, mixed frequency data, time-varying parameters, non-linearities, non-stationarity, and many other characteristics often observed in real systems of economic variables. The main contribution of this paper is to provide a comprehensive updated summary of the literature on latent common factors extracted using KFS procedures in the context of dynamic factor models, pointing out their potential limitations. Signal extraction and parameter estimation issues are separately analyzed. Identification issues are also tackled in both stationary and non-stationary models. Finally, empirical applications are surveyed in both cases. This survey is relevant to researchers and practitioners interested not only in the theory of KFS procedures for factor extraction in dynamic factor models but also in their empirical application in macroeconomics and finance.     

Exploring the mismatch between credit ratings and loss-given-default: A credit risk approach

It is commonly observed that high grade loans with better ratings are often associated with low recoveries if they default (i.e. with relatively high loss-given-default (LGD)). To address the mismatch problem, this paper proposes a credit risk approach by minimizing LGD for higher rated loans as a risk-rating matching standard in the sense that the decreasing LGD from creditors’ perspective is associated with higher credit rating for the borrower. This standard forces customers’ credit rating of each grade to be optimally determined in correspondence to its LGD, which means the LGD of high grade loans tends to be low. The approach is then tested using three credit datasets from China, i.e. credit data from 2044 farmers, 2157 small private businesses and 3111 SMEs. The empirical results show that the proposed approach indeed guides the way to solve the mismatch phenomenon between credit ratings and LGDs in the existing credit rating literature. By optimally determining credit ratings, the findings derived from this paper help provide a valuable reference for bankers, and bond investors to manage their credit risk.     

Optimal capacity and operation design of a robot logistics system for the hotel industry

This study introduces an optimal capacity and operation design of a robot logistics system that can reduce human workload in the hotel industry. In hotels, there are several duties that can be replaced by robots such as accompanying guests to the certain areas, delivering specific items to the guest rooms, and transporting some items that guests want to be removed from the guest rooms. To apply the robot logistics system in the hotel industry, the capacity and operation design should be prepared adequately. For that, a mathematical model-based optimization technique is used to decide the number of robots with the concept of minimizing total investment cost and to derive the optimal job assigning with the purpose of maximizing total covered jobs. In addition, a numerical example is performed to validate the proposed mathematical model and the sensitivity tests are examined to reflect the random features.     

基于改进指纹聚类的WLAN定位优化方法

将K-means聚类算法应用到无线局域网（WLAN）位置指纹定位中，虽然可以缩短定位时间，但是容易降低定位精度。为了解决此问题，提出了基于改进指纹聚类的WLAN定位优化方法。首先根据接收信号强度标准差来优化初始聚类中心的选取,然后对指纹数据进行聚类处理,最后进行在线定位。实验结果表明，与传统的WLAN位置指纹定位方法和K-means聚类定位方法相比，基于改进指纹聚类的定位优化方法不仅缩短了定位时间，还能有效提高定位精度。     

Research on a diagnostic system of rural vitalization based on development elements in China

In 2017, the Chinese government implemented a national strategy of "Rural Vitalization" that sought to realize full-scale rural vitalization. However, is it possible to achieve vitalization for all the villages in China? How should their development potential be determined? This paper identified and analyzed the "element-composite" messages of rural development based on 99 exemplary sites of “Beautiful Villages” in China. Combined with the projection pursuit classification method, a diagnostic system of rural vitalization was established; then, Dehua County was taken as a case study for an in-depth analysis. Based on national data analysis, the final results indicated that livelihood resources (LR), agglomeration effects (AE), location and transportation (LT), cultural/natural landscapes (CN), and economic circumstance (EC) are essential elements for successful rural development. Additionally, EC was the only exogenous element, while the remaining elements were endogenous. Furthermore, the villages with better EC presented urbanization rates of 38∼82 % and Engel coefficients of 29∼41 % in their counties; exemplary sites lacking LR, CN, LT, and AE account for 13.13 %, 19.19 %, 26.26 %, and 60.61 % respectively, so the indispensability of these elements decreases progressively in sequence. Only 2 % of villages rely on single element for success, therefore, the composite pattern of development element was also critical; 10 out of 16 types were found to successfully facilitate village development, among which, the type of R-a-L-C (32.32 %) and R-A-L-C (15.15 %) were considered as the greatest potential patterns for vitalization. Finally, by means of the diagnostic system, the ratio of representative villages for high-low potential in Dehua County is evenly split; then, development paths, and land use policies that match with paths were proposed, on the basis of development potential and “element-composite” condition of themselves.     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.     

Waste of money or growth opportunity: The causal effect of EU subsidies on Hungarian SMEs

Although EU subsidies aiming at economic development play a pivotal role not only for Hungary but for the entire European Union as well, there is a debate regarding their effectiveness in the literature. This paper investigates the impact of direct economic development subsidies extended in the context of Structural Funds and the Cohesion Fund as part of the 2007–2013 programming period of the European Union on Hungarian micro, small and medium-sized enterprises. Based on a micro database, we evaluate the impact of corporates’ first subsidies on various performance indicators, using a combination of propensity score matching and fixed effects panel regression. According to our results, economic development funds had a significant positive effect on the number of employees, sales revenue, gross value added and, in some cases, operating profit. However, the labour productivity of enterprises was not significantly affected by any of the support schemes. Furthermore, by explicitly comparing non-refundable subsidies (grants) and refundable assistance (financial instruments), we find that there is no significant difference in the effectiveness of the two types of subsidy.     

基于两阶段法的多车型卷烟配送路径优化研究

在烟草商业企业中,物流是其重要的环节,是连接客户与烟草企业间的纽带,其卷烟配送线路设计的合理与否直接影响到卷烟的配送效率和配送成本,就如何合理的规划线路成为卷烟配送的关键问题。文章以Q烟草公司为例,运用先分组后路线的两阶段法对问题进行求解,先利用K-means聚类算法对区域进行划分,再考虑工作量均衡的条件下引入遗传算法对区域进一步调整,最后利用混合遗传算法对各配送区域进行线路优化,通过实例从线路数、车辆数、空载率、配送里程及总成本等指标上可以看出两阶段法的配送效果更优。     

GNSS抗干扰技术综述

随着电磁环境的日益复杂、干扰技术的不断进步，全球卫星导航系统（Global Navigation Satellite System，GNSS）的各类应用受到了严重阻碍，在强干扰环境中，扩频增益不足以对干扰进行有效抑制，需采用各种抗干扰措施。对GNSS抗干扰技术进行了分类，概述了不同抗干扰技术的研究现状及进展，并对GNSS干扰源与干扰类型进行了归纳总结，给出了不同干扰类型对应的抗干扰方法，进一步对比分析了几类常见自适应算法的性能，最后指出了GNSS抗干扰技术未来的研究趋势。