Green consumption behavior prediction based on fan-shaped search mechanism fruit fly algorithm optimized neural network

Predicting consumption behavior is very important for adjusting supplier production plans and enterprise marketing activities. Conventional statistical methods are unable to accurately predict green consumption behavior because it is characterized by multivariate nonlinear interactions. The paper proposes an optimized fruit fly algorithm (FOA) and extreme learning machine (ELM) model for consumption behavior prediction. First, to address the problem of uneven search direction of FOA leading to insufficient search ability and low efficiency, the paper proposes a sector search mechanism instead of a random search mechanism to improve the global search ability and convergence speed of FOA. Second, to address the issue that the initial weights and hidden layer bias values of the ELM are randomly generated, which affects the learning efficiency and generalization of the ELM, the paper uses an improved FOA to optimize the weights and bias values of ELM for improving the prediction accuracy. Taking the green vegetable consumption behavior of Beijing residents as an example, the results show the optimization of the initial weight and threshold of ELM by the GA, PSO, FOA, and SFOA, the prediction accuracy of the GA-ELM, PSO-ELM, FOA-ELM, and SFOA-ELM models all surpass those of ELM. Compared with BPNN, GRNN, ELM, GA-ELM, PSO-ELM, and FOA-ELM models, the RMSE value of SFOA-ELM was decreased by 9.45%, 8.40%, 11.89%, 5.84%, 2.22%, and 2.69%, respectively. These findings demonstrate the effectiveness of the SFOA-ELM model in green consumption behavior prediction and provide new ideas for the accurate prediction of consumption behaviors of other green products with similar characteristics.     

建章宫“一池三山”之仙山形态试探

建章宫“一池三山”的布局源于汉武帝的神仙信仰。受此影响，其中的仙山形象应是上广中狭的台状构筑物。此种台状仙山与汉代慕拟自然的假山形象并行发展，成为后世皇家园林“一池三山”的主要表达方式。通过对汉代图像资料中的仙山形象进行梳理，并结合相关的文献记载，对“一池三山”的仙山形态进行探究。进而分析了这一仙山形态在古典园林仙境景观中的发展演变，及其与汉代园林中用于迎仙的台的区别与联系，为进一步理解早期园林中的景观内容提供新的线索。     

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.     

基于模糊多属性群决策的维护方式选择研究

维护方式选择是维护管理中的重要工作之一,合理的维护方式既能达到保障设备的稳定运行,又能同时兼顾其它各个方面的要求。由于对维护方式的评价涉及多个部门、人员和属性,有些指标只是一个模糊的概念,因而采用模糊多属性群决策的方法对维护方式进行优先抉择。本文结合A公司的设备维护方式选择问题,尝试使用模糊多属性群决策折衷算法求解最佳的维护方式。     

Optimal distribution of the injured in a multi-type transportation network with damage-dependent travel times: Two metaheuristic approaches

We study a location-allocation-routing problem for distribution of the injured in a disaster response scenario, considering a three-type transportation network with separate links. A circle-based approach to estimate the impacts of the disaster is presented. After formulating relations for computing the percentage of the injured, the destruction percentage and the damage-dependent travel times, the problem is formulated as an integer nonlinear program. We utilize a genetic algorithm and a discrete version of the imperialist competitive algorithm for solving large problems. An empirical study focused on earthquakes in Tabriz, Iran, illustrates applicability of the proposed model and performance of the proposed algorithms.     

The function-specific microfoundations of dynamic capabilities in cross-border mergers and acquisitions

In mergers and acquisitions, the acquiring firm must combine two firms’ resources and capabilities so that the outcome yields value. In individual firms, the marketing & sales, and R&D functions have typically developed intertwined and complex relationships over time. These multifaceted dependencies may obscure the integration of the firms and their functions. In order to reveal to what extent cross-functional relationships determine the success or failure of an acquisitions, we have made one of the first attempts to study merging firms’ function-specific capabilities, underlying microfoundations, and their cross-functional relationships during the integration process—instead of focusing on acquisition capabilities as such. We use longitudinal data from two cross-border acquisitions between US and Finnish SMEs. Our results indicate that major differences between merging firms’ cross-functional microfoundations—that is, their structures, processes, routines, and skills—might either enforce or erode the seemingly promising synergies at the product and market levels, depending on managerial awareness of their nature.     

Does ethics improve stock market resilience in times of instability?

This paper compares the resilience of ethical (Islamic and socially responsible) indexes among five developed (US, UK, Japan, Canada, Australia) and three emerging markets (Brazil, India, South Africa) during the period following the 2008 subprime crisis. It relies on a multivariate CAPM-EGARCH model that accounts for sudden changes in volatility through the application of an iterated cumulative sums of squares (ICSS) algorithm on daily data over the sample period 2008–2014 to model time-varying volatility and ensure reliable estimates. The study confirms the lower systemic risk associated with Islamic indexes during the bearish period and reports that SRI, despite being more subject to systemic risk, offered higher alphas in highly integrated markets, while Islamic indexes performed better in less integrated ones. The evidence also reveals a very limited increase in the models’ predictability power from the integration of sudden changes in volatility into the EGARCH models during the full sample period. This limit is more marked during the bearish sub-period. Our findings have important implications for international investment and portfolio diversification perspectives in times of financial downturn.     

Perceptions of the benefits of the A3 planner in facilitating project-based learning in accounting education

This paper evaluates ways of instilling project management skills into accounting-based learning by the use of an iterative A3 planner to plan, monitor and review assignment progress. The application of an A3 planner to facilitate a project-based learning (PBL) group assignment in undergraduate accounting education has been critically evaluated in terms of both the student and tutor experience. The study uses a mix of qualitative and quantitative data. Quantitative data assisting exploration of perceptions were collected through 100 undergraduate students. A series of focus group discussions were carried out to investigate students’ engagement and tutors’ teaching experiences regarding the adoption of the A3 planner. The results suggest that the A3 planner promotes active planning and effective management of a PBL group assignment. It makes students’ thought processes more visible thereby facilitating and enhancing the tutoring/mentoring process. Moreover a more interactive and transparent approach by doing assignment via the use of an iterative A3 planner has ensured more feedback points and action based efficiency in the doing approach for learners.     

一种动态加权的LDPC译码方法

为了加快低密度奇偶校验（LDPC）码的译码速度，有效改善LDPC码的译码性能，针对校验节点更新过程中的对数似然比（LLR）值的大小，设计了一种LDPC码的动态加权译码方法。以IEEE 802.16e标准的奇偶校验矩阵为例，根据LLR值的变化规律，利用增长因子和抑制因子对和积译码算法和最小和译码算法进行动态加权。仿真结果显示，基于动态加权的译码方法相对于传统译码方法误码率都有明显改进，译码复杂度也有所降低。     

Exploring the development trend of internet finance in China: Perspective from club convergence

We first employ β-conditional convergence and log t regression tests based on nonlinear time-varying factor model and club clustering algorithm to analyze the convergence characteristics of the development level of Internet finance in 335 prefecture-level cities in China. The result of log t regression test illustrates that there is no convergence as a whole in the development level of China's Internet finance. However, seven convergence clubs and a divergent group have been formed, and the development level and growth rate of Internet finance among these convergence clubs have shown obvious differences. Moreover, we also employ the Ordered Probit to explore the formation mechanism of the convergence clubs. The results reveal that the regions with a higher level of economic development, traditional financial development, economic openness and Internet development are more inclined to converge in a club with a higher Internet finance development level. Alternatively, the regions that are interfered with more by the government or that have a lower degree of marketization, tend to converge in a club with a lower level. Finally, according to the conclusions, we propose corresponding policy recommendations for promoting the regional coordinated development of China's Internet finance.