基于消息队列和XML的数据同步技术研究

数据同步技术一直是影响分布式计算机系统应用的一个决定性因素,在简单介绍了现有的数据同步技术的基础上,提出了采用Windows的消息队列和二进制XML编码技术相结合的数据库同步方案,给出了具有较高数据压缩比率的二进制XML编码算法,实现了在窄带网络环境下的数据同步,并对数据同步的导入导出策略进行了设计,仿真测试的结果表明该同步算法相较于传统的数据同步算法具有很好的网络传输特性及数据同步的可靠性,这些对于数据同步技术的研究,在理论与实践上都有一定的借鉴意义。     

基于消息队列和XML的数据同步技术研究

数据同步技术一直是影响分布式计算机系统应用的一个决定性因素,在简单介绍了现有的数据同步技术的基础上,提出了采用Windows的消息队列和二进制XML编码技术相结合的数据库同步方案,给出了具有较高数据压缩比率的二进制XML编码算法,实现了在窄带网络环境下的数据同步,并对数据同步的导入导出策略进行了设计,仿真测试的结果表明该同步算法相较于传统的数据同步算法具有很好的网络传输特性及数据同步的可靠性,这些对于数据同步技术的研究,在理论与实践上都有一定的借鉴意义。     

Liquefied natural gas importing security strategy considering multi-factor: A multi-objective programming approach

LNG importing strategies, in the literature, are primarily studied under a common single-factor framework. However, LNG importing strategies are affected by a variety of factors. To address this existing gap, this paper proposes a Multi-Objective Programming model, which takes into account the cost, the country risk, the shipping risk, and the impact of extreme events. A pure structural change model is used to determine the risk impact coefficient for extreme events. An enhanced Simulated Annealing Algorithm is then used to solve the LNG-importing optimization problem. An experimental study is further conducted to verify the practicability of the proposed approach in the case of China's LNG-importing data. The software implementation of the proposed model is developed in Python. The proposed model provides a decision support tool for LNG importing companies to find an efficient portfolio strategy for LNG importing. The optimization model can be used for analyzing similar scenarios involving such dimensions as economy, energy security, and especially energy diversification.     

基于文本向量化方法构建IT运维服务台事中处置参考模型

针对传统IT运维服务平台事件全文检索准确度不高及大量历史事件单再利用率低的特点,提出一种基于事件文本向量化处理方法的事中处置参考模型.通过建立生产运维特征词库,将事件工单文本表示成特征向量,并选择合适的算法对不同事件文本特征向量进行相似度计算,最终通过匹配找到平台历史事件或者知识库中与现有事件相似度高的事件或知识,供故障处置人员参考.将此方法应用到企业级服务台事件处置流程中,能帮助运维人员快速准确地找到类似的历史事件或者相关的知识,形成事中处置参考,加快事件处置效率,同时也进一步提高了运维工具的智能化水平.     

基于知识分层提取模型的服务台知识库建设

针对传统运维知识库建设的不足,提出了一种面向服务台的生产运维知识自动分层提取模型。通过建立生产运维特征词库,对事件工单的短文本进行向量化解析,并利用改进的 KNN 算法实现事件短文本分类,最终通过领域主题规则完成知识的发现。将此方法应用到企业级服务台知识库建设中,完成了由事件工单到知识的自动转化,弥补了手工创建知识的缺陷,促进了整个运维流程的自动化。     

浅谈数据中心开放平台监控集成系统的设计

由于数据中心开放平台生产环境使用了多种监控软件,不利于监控信息的有效管理、处置、决策,需要开发一个数据中心开放平台监控集成系统对监控信息进行整合,以便提高报警问题处理的预判性、规范性。开发过程中采用了标准C及C#开发语言,使用到C/S架构及TongLink中间件技术。整体架构中,主要有采集服务器、分析服务器、数据库服务器、Web服务器以及客户端。其中采集服务器负责汇聚报警信息,分析服务器负责分析及过滤处理等工作。监控集成系统投产后,情况良好,提升了数据中心开放平台的运维保障与管理能力。     

Optimal reactive power dispatch problem using a two-archive multi-objective grey wolf optimizer

In this paper, a novel two-archive Multi-Objective Grey Wolf Optimizer (2ArchMGWO) is proposed for solving Multi-Objective Optimal Reactive Power Dispatch (MORPD) problems. The optimizer has been improved from its original Multi-Objective Grey Wolf Optimizer (MGWO) by modifying the reproduction operator and adding the 2-archive concept to the algorithm. It is then implemented on solving MORPD with objective functions being active power loss minimization and voltage profile improvement (voltage deviation minimization). The generator bus voltages, tap setting transformers and shunt reactive power sources or flexible alternating current transmission systems are set as design variables. The proposed algorithm along with other existing multiobjective optimizers are applied to solve three test problems with the standard IEEE 30-bus, IEEE 57-bus, and the IEEE 118-bus power systems. The optimum results obtained from the various optimizers performance are compared based on the hypervolume indicator and they reveal that 2ArchMGWO is clearly superior to the others.     

用NPOI完成对Excel含匹配字符串行的筛选

讲解采用NPOI及C#编程语言实现筛选Excel中含有匹配字符串行。     

Developing an advanced ANN-based approach to estimate compaction characteristics of highway subgrade

The current methodology of assessing the compaction characteristic of subgrade fillers is time-consuming. The spot-sampling method and the following laboratory tests bring bias to engineering practice. This study proposes an advanced approach to determine the maximum dry density, optimum moisture content, and compactness of subgrade based on ANN algorithms. A large number of compaction tests are performed to assess the compaction quality of various types of subgrade fillers. The particle gradation is specifically considered. Wave propagations of the compacted specimen are assessed based on the ultrasonic test, and the anisotropic feature is demonstrated. The dynamic elastic parameters are derived to further reveal the interaction mechanism. A dataset is proposed by combining these laboratory data and the literature data. The PSO-BP-NN model is developed to automatically predict the compaction parameters of different filling materials. A positive correlation is demonstrated between the elastic modulus and the total density, and Poisson’s ratio illustrates an inverse trend. The compaction energy is influential to the maximum dry density while the moisture content has the greatest impact on the compactness. This study aims to develop an accurate model to replace the extensive Proctor test and efficiently evaluate the compaction quality of subgrade for highway constructions.     

Integrate design structure matrix with carbon footprint for product low carbon design

Product low-carbon design plays a significant part in reducing carbon footprint during the product life cycle. This paper proposed Design Structure Matrix integrated with Carbon Footprint (DSM-CF) to design for low carbon footprint. After the carbon footprint for product life cycle is discussed in detail, the DSM-CF is also proposed. The construction, decomposition and clustering algorithm of DSM-CF model is then put forward in detail. The impact of the carbon footprint of each design task on the entire product life cycle is analyzed, which could effectively reduce the carbon footprint of products. At the end of this paper, the DSM-CF model of the hand rehabilitation robot system is established to verify the effectiveness of the model.