福建省加权网络应急物资储备点选址

文章在对应急物资储备点选址模型进行概述的基础上,对福建省应急物资储备点进行了分析。选择集合覆盖和加权网络作为理论基础实现储备点选址。并给出福建省应急物资储备点选址的最优方案和遍历应急系统所有区域所需要的时间。     

Stochastic leader–follower DEA models for two-stage systems

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). In recent years, it has been widely used to evaluate two-stage systems under different organization mechanisms. This study modifies the conventional leader–follower DEA models for two-stage systems by considering the uncertainty of data. The dual deterministic linear models are first constructed from the stochastic CCR models under the assumption that all components of inputs, outputs, and intermediate products are related only with some basic stochastic factors, which follow continuous and symmetric distributions with nonnegative compact supports. The stochastic leader–follower DEA models are then developed for measuring the efficiencies of the two stages. The stochastic efficiency of the whole system can be uniquely decomposed into the product of the efficiencies of the two stages. Relationships between stochastic efficiencies from stochastic CCR and stochastic leader–follower DEA models are also discussed. An example of the commercial banks in China is considered using the proposed models under different risk levels.     

Metafrontier efficiency analysis for hospital pharmacy services using dynamic network DEA framework

Medication management is a complex but critical process within the healthcare delivery system. The pharmacy department in healthcare facilities is responsible for acquisition, distribution and dispensing of medication to patients that involves a series of network process. This process can be categorized into two main subprocesses: i) pharmacy store and ii) patient services (i.e., ambulatory and inpatient pharmacy). The objective of this study was to investigate the relative efficiency level of the two subprocesses of pharmacy services in Malaysia's public hospitals. We used a nonconvex metafrontier technology to estimate technical efficiency of hospital pharmacies between specialist and nonspecialist hospital categories under the dynamic network data envelopment analysis (DNDEA) framework. For overall efficiency, both specialist and nonspecialist categories had similar mean efficiency scores. However, when measuring the efficiency level according to pharmacy store and patient services separately, the nonspecialist category had a higher mean efficiency score in pharmacy store, whereas for patient service efficiency, both categories had similar results. The patient service efficiency level was lower consistently over time, suggesting that the overall inefficiency of hospital pharmacy is greatly influenced by the inefficiency of the patient service. This suggests that systematic improvements in patient service efficiency should be a higher priority than pharmacy store efficiency to further increase the overall efficiency level. We believe that our findings will provide valuable information to policymakers towards achieving an efficient public healthcare service.     

移动网络数据中大数据处理的关键技术探索

最近几年以来,我国科技水平持续提升,计算机网络技术也逐渐在各行各业中获得了广泛运用,这也使得信息技术的深度融合发展受到一定的促进,数据规模愈发庞大,在此背景下,开始演变成大数据供不应求的状况.为此,国内陆续推出了一系列相关的管理法规与条例,同时扩大了对大数据的探究创新力度,有效提升了移动通信网络处理数据的速度,这同时促...     

基于BP人工神经网络的绿色施工模糊综合评价研究

发展绿色施工促进施工企业节约能源和资源、保护环境,是全球应对气候变化挑战、实现可持续发展的重要手段,而绿色施工评价对于建筑业落实可持续发展起到一定作用。本文在介绍BP人工神经网络基本原理的基础之上,分析了与其它评价方法相比,BP人工神经网络在绿色施工评价中的优越性。通过建立模糊评价矩阵,利用BP人工神经网络处理数据,较客观地对绿色施工进行评价。最后将此评价模型应用于实例,取得了令人满意的结果。     

工程建设施工现场中3G视频监控系统的研究与实现

随着建筑行业的飞速发展,施工现场的安全问题一直是工地管理工作的重中之重。网络技术的发展,使得视频监控系统运用到各行各业中。通过运用远程视频监控技术,实时对分布在各地的多个施工现场进行监管,既减轻了管理人员的工作量,又加强了建设行政主管部门以及施工和安全质量监督管理部门的监管力度。安全管理是建筑工地的重要管理环节,考虑到工地实际需求,本文针对传统视频监控系统实时性差、传输效率低、图像质量不稳定等缺点,对基于3G网络的工程建设施工现场远程视频监控系统进行研究和实现。文中介绍了3G网络的无线视频技术的优势及远程视频监控系统的功能特点,对施工现场3G远程视频监控系统的方案进行研究设计,并在某施工单位几个重点施工现场进行了试点安装,达到了预期效果,实现对施工现场实时监控。     

论物流客户关系网络管理

从物流客户关系网络管理的产生入手,对基于网络的物流客户细分和物流客户关系网络管理的关键技术网络数据挖掘在物流客户关系网络管理中作用及功能进行分析,在此基础上建构物流客户关系网络管理系统。     

On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks

Daily and weekly seasonalities are always taken into account in day-ahead electricity price forecasting, but the long-term seasonal component has long been believed to add unnecessary complexity, and hence, most studies have ignored it. The recent introduction of the Seasonal Component AutoRegressive (SCAR) modeling framework has changed this viewpoint. However, this framework is based on linear models estimated using ordinary least squares. This paper shows that considering non-linear autoregressive (NARX) neural network-type models with the same inputs as the corresponding SCAR-type models can lead to yet better performances. While individual Seasonal Component Artificial Neural Network (SCANN) models are generally worse than the corresponding SCAR-type structures, we provide empirical evidence that committee machines of SCANN networks can outperform the latter significantly.     

Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx

We extend neural basis expansion analysis (NBEATS) to incorporate exogenous factors. The resulting method, called NBEATSx, improves on a well-performing deep learning model, extending its capabilities by including exogenous variables and allowing it to integrate multiple sources of useful information. To showcase the utility of the NBEATSx model, we conduct a comprehensive study of its application to electricity price forecasting tasks across a broad range of years and markets. We observe state-of-the-art performance, significantly improving the forecast accuracy by nearly 20% over the original NBEATS model, and by up to 5% over other well-established statistical and machine learning methods specialized for these tasks. Additionally, the proposed neural network has an interpretable configuration that can structurally decompose time series, visualizing the relative impact of trend and seasonal components and revealing the modeled processes’ interactions with exogenous factors. To assist related work, we made the code available in a dedicated repository.     

产业集群的区域创新网络系统分析

区域创新是一个区域获得可持续发展的根本动力,区域创新能力正日益成为区域经济获取国际竞争优势的决定性因素和区域经济具备竞争优势的重要标志。作为区域经济重要形态的产业集群,以其显著的网络特性成为区域创新系统的理想处所,而构建区域创新系统已经成为各区域实现快速发展的战略选择。本文从产业集群出发,研究创新网络系统的构成及其运行机制,并提出了构建区域创新网络系统的几点思路。