变电设备红外线热成像诊断技术的准确性分析

红外诊断技术是一种新型诊断技术,为变电设备的热诊断提供了很好的诊断方式,该种诊断方式有着不解体、直观性、快速性、准确性的特征,也适宜用在大面积检测中,同时,该种诊断技术也能够与其他检测方式联合使用,定位故障的具体位置,这就可以有效提升检修的便利性。但是,影响红外线热成像诊断技术准确率的因素是多种多样的,在进行诊断时,必须要合理地控制其测量环境与测量方式。本文主要分析影响红外线热成像诊断技术准确性的因素,并提出相关的解决措施。     

The M4 Competition: Results,findings, conclusion and way forward

The M4 competition is the continuation of three previous competitions started more than 45 years ago whose purpose was to learn how to improve forecasting accuracy, and how such learning can be applied to advance the theory and practice of forecasting. The purpose of M4 was to replicate the results of the previous ones and extend them into three directions: First significantly increase the number of series, second include Machine Learning (ML) forecasting methods, and third evaluate both point forecasts and prediction intervals. The five major findings of the M4 Competitions are: 1. Out Of the 17 most accurate methods, 12 were “combinations” of mostly statistical approaches. 2. The biggest surprise was a “hybrid” approach that utilized both statistical and ML features. This method’s average sMAPE was close to 10% more accurate than the combination benchmark used to compare the submitted methods. 3. The second most accurate method was a combination of seven statistical methods and one ML one, with the weights for the averaging being calculated by a ML algorithm that was trained to minimize the forecasting. 4. The two most accurate methods also achieved an amazing success in specifying the 95% prediction intervals correctly. 5. The six pure ML methods performed poorly, with none of them being more accurate than the combination benchmark and only one being more accurate than Naïve2. This paper presents some initial results of M4, its major findings and a logical conclusion. Finally, it outlines what the authors consider to be the way forward for the field of forecasting.     

云财务共享服务模式设计——以费用报销流程为例探讨

在企业数量增加的同时,企业之间所具有的竞争情况也愈发激烈。其中,财务共享服务是目前企业提升运营效率、降低运营成本的一项重要方式。本文中就以企业的费用报销流程为例对云财务共享服务模式进行一定的研究与设计。     

A HPC based cloud model for real-time energy optimisation

Recent research has emphasised that an increasing number of enterprises need computation environments for executing HPC (High Performance Computing) applications. Rather than paying the cost of ownership and possess physical, fixed capacity clusters, enterprises can reserve or rent resources for undertaking the required tasks. With the emergence of new computation paradigms such as cloud computing it has become possible to solve a wider range of problems due to their capability to handle and process massive amounts of data. On the other hand, given the pressing regulatory requirement to reduce the carbon footprint of our built environment, significant researching efforts have been recently directed towards simulation-based building energy optimisation with the overall objective of reducing energy consumption. Energy optimisation in buildings represents a class of problems that requires significant computation resources and generally is a time consuming process especially when undertaken with building simulation software, such as EnergyPlus. In this paper we present how a HPC based cloud model can be efficiently used for running and deploying EnergyPlus simulation-based optimisation in order to fulfil a number of objectives related to energy consumption. We describe and evaluate the establishment of such an application-based environment, and consider a cost perspective to determine the efficiency over several cases we explore. This study identifies the following contributions: (i) a comprehensive examination of issues relevant to the HPC community, including performance, cost, user perspectives and range of user activities, (ii) a comparison of two different execution environments such as HTCondor and CometCloud and determine their effectiveness in supporting simulation-based optimisation and (iii) a detailed performance analysis to locate the limiting factors of these execution environments.     

云计算相关问题及其在高校中的运用价值

云计算是计算机科学技术与网络互联技术结合创新发展的产物,已经成为引领未来世界信息产业的关键性技术和手段。云计算在教育领域体现出了很大优势,改进学习方式,改造学习环境,同时可以降低IT成本,对于提高高校现有资产的效率、利用率和灵活性具有重要影响意义。     

浅谈选煤厂建设投资估算影响因素及改进措施

本文对选煤厂建设工程投资估算中影响准确性的因素进行了分析,并结合BP神经网络理论基于Matlab软件对选煤厂带式输送机及栈桥单位工程进行了数值模拟,通过对比数值模拟结果与概算指标估算结果,详细阐述了可以提高选煤厂建设工程投资估算准确性的几点建议。     

基于云重心Shapley值的供应链融资联盟收益分配研究

针对Shapley值法在供应链融资联盟收益分配过程中分配因素考虑不全以及各分配因素随机性和模糊性强的缺点，本文利用云重心法修正Shapley值的收益分配。根据供应链融资联盟收益分配的主要影响因素，在传统的Shapley值法的基础上引入了风险系数、投入成本、努力程度以及信息对称水平4个分配修正因子，弥补了影响因素的缺失，并利用云重心法计算各联盟企业的收益修正值，云重心法能够解决定性指标和定量指标之间的模糊性转换，极大克服了Shapley值法自身的局限性。算例对比结果发现，改进的Shapley值法能更加合理的分配收益，有利于维持供应链融资联盟的稳定。     

Modelling property values in Nigeria using artificial neural network

Unreliable and inaccurate property valuation has been associated with techniques currently used in property valuation. A possible explanation for these findings may be due to the utilisation of traditional valuation methods. In the current study, an artificial neural network (ANN) is applied in property valuation using the Lagos metropolis property market as a representative case. Property sales transactions data (11 property attributes and property value) were collected from registered real estate firms operating in Lagos, Nigeria. The result shows that the ANN model possesses a good predictive ability, implying that it is suitable and reliable for property valuation. The relative importance analysis conducted on the property attributes revealed that the number of servants’ quarters is the most important attribute affecting property values. The findings suggest that the ANN model could be used as a tool by real estate stakeholders, especially valuers and researchers for property valuation.     

Measuring the shopper's attitude toward the point of sale display: Scale development and validation

In Europe alone, marketers invest several hundred million of Euros in marketing activities at the point of sale every year. A prominent role is assigned to display promotions. However, despite their large practical importance, surprisingly, there is no measure to pre-evaluate different displays and their design facets so that the display which reached the best pre-evaluation results may be identified and, if poor rated facets were found, those may be altered before production and rollout of the display in question. Therefore, this paper develops and validates a scale to measure the shopper's attitude toward a point of sale display reflecting all relevant facets of a display from the shopper's point of view. Examination of the scale led to satisfactory results in terms of reliability, validity, and its predictive power for purchase intention. Summarizing, the scale can help to improve display designs prior to rollout, thus, enhancing the efficiency of display promotions.     

基于云计算的民族地区高校教育信息化平台建设研究——以贵州省为例

教育信息化程度成为了国家教育现代化程度的风向标,本文以"云计算"技术为抓手,从教育工作的流程出发,设计教育资源及教育管理两个平台。通过两个云平台的建设,夯实智慧教育基础,为智慧教育的应用开发提供强有力地保障。