舰艇编队海上物资再补给目标优化研究

为对舰艇编队的物资的再补给过程进行优化研究,首先,分析了舰艇编队物资补给的全过程,阐述了物资再补给的必要性;其次,将常见的应急物资调度问题与海上物资再补给问题进行比较,分析二者的联系与区别;接着,基于海上再补给对物资的要求,以再补给任务完成时间最短及物资调度总成本最小为目标建立优化模型,并类比应急物资调度中出救点的组合优化问题进行算法设计;最后,以某舰艇编队实施常规再补给任务为例,运用所设计的算法进行求解,得出合理的规划方案。结果验证了算法的有效性以及运用算法解决海上物资再补给问题的可行性。     

大型船舶物资补给可视化仿真

大型船舶物资补给可视化仿真可以形象地模拟物资补给搬运流程, 计算搬运时间, 发现搬运中的瓶颈问题, 进而实现搬运流程优化. 在定性分析大型船舶物资补给类型和搬运流程的基础上, 提出了基于Flexsim的大型船舶物资补给可视化仿真体系结构, 设计了仿真模型, 探讨了仿真平台实现的关键技术. 结合具体的案例, 开展了仿真实验, 结果表明, 可视化仿真对于大型船舶物资补给物料搬运系统的设计和运行管理具有重要作用.     

解析大数据的协议库存物资需求预测体系

当前电力行业的物资需求量大,为了确保电力企业的物资供应,建立物资需求预测体系非常重要的环节,物资需求是否准确将直接关系到企业的运营成本以及电力行业的工程进度。物资需求预测体系可以从物资上报前进行预测,于物资上报期间进行分析以及上报后挖掘等方面,在大数据的环境下进行建立。本文采用大数据的方法,针对电力企业的协议库存物资需求预测体系进行简要分析。     

Web数据挖掘工具及其在电子商务中的应用

该工具是辅助电子商务网站开发的综合分析工具,运行在电子商务网站的用户数据库和数据仓库之上。包括以下功能模块: 过滤器:用来从Web数据库中抽取相关数据,进行二义性分析,消除不一致性。 挖掘综合器:是一个挖掘驱动引擎。根据挖掘要求和挖掘方法的知识库到Web数据挖掘算法库中去选择合适的挖掘方法,并且使用该方法去执行挖掘任务。     

Web使用挖掘研究

Web数据挖掘是数据挖掘技术在Web信息仓库中的应用与研究。Web数据挖掘包括Web内容挖掘、Web结构挖掘和Web使用挖掘三个研究方向,文中研究的重点是Web使用挖掘。Web使用挖掘研究的主要对象是用户的使用记录,研究的主要过程包括数据预处理、模式发现和模式分析。文中详细介绍了Web使用挖掘的最新研究成果,并对将来技术的研究方向和发展趋势进行了探讨性的预测与分析,为进一步的理论研究和实际应用工作提供了指导性的建议。     

Web使用挖掘研究

Web数据挖掘是数据挖掘技术在Web信息仓库中的应用与研究.Web数据挖掘包括Web内容挖掘、Web结构挖掘和Web使用挖掘三个研究方向,文中研究的重点是Web使用挖掘.Web使用挖掘研究的主要对象是用户的使用记录,研究的主要过程包括数据预处理、模式发现和模式分析.文中详细介绍了Web使用挖掘的最新研究成果,并对将来技术的研究方向和发展趋势进行了探讨性的预测与分析,为进一步的理论研究和实际应用工作提供了指导性的建议.     

加权增量关联规则挖掘在通信告警预测中的应用

针对通信网络告警预测中预测精度不高、模型训练效率较低等缺陷,提出告警权值确定方法和基于自然序树（Can-tree）的加权增量关联规则挖掘的通信网络告警预测方案。首先,对告警数据进行预处理,确定告警数据权值并压缩到Can-tree结构中;其次,应用增量关联规则挖掘算法对Can-tree进行挖掘,生成告警关联规则;最后,使用模式匹配的方法对实时告警信息进行预测,并对结果进行优化整理。实验结果表明,基于Can-tree的加权增量关联规则挖掘算法是高效的,利用前次挖掘的结果和信息提高了挖掘的效率,网络告警数据的权值分配方案能够合理地区分告警数据的重要程度,有助于将重要程度高的告警关联规则挖掘出来,并加快过时告警关联规则的淘汰,提高预测的准确度和精度。     

数据挖掘技术下的银行客户流失决策树预测算法

在银行客户流失预测系统中经常要通过客户数据对未知客户的服务信息进行预测,以对银行今后的经营策略提供依据。在对客户的预测中,经常需要对他们的某种分类属性进行分类规则挖掘。该文主要探讨使用决策树这种常用的有效的方法来对客户数据进行分类规则挖掘。     

一个数据挖掘工具的设计与实现

数据挖掘是一个利用各种分析工具在海量数据中发现模型和数据间关系的过程，这些模型和关系可以用来做出预测，该文介绍了一人数据挖掘工具的设计，以Apriori算法为核心，实现了数据挖掘中基于数据库的几种常用挖掘方法，包括基于关系数据库的数据挖掘，不完整数据库中的数据挖掘和根据兴趣度测量来挖掘感兴趣知识的异常关联规则挖掘。     

基于支持向量机回归的应急物资需求预测

目前对应急物资需求预测仍以专家经验判断为主,尚未形成成熟的办法.针对应急物资预测方法缺乏科学依据难题,提出了一种新的科学预测方法-两步法,即支持向量机回归算法和库存管理模型,建立了人员伤亡预测模型,对地震人员伤亡进行了预测,然后再结合库存管理模型对应急物资进行了估算.最后,运用提出的方法对“青海玉树地震”的人员伤亡进行了预测,证明了方法的有效性,并估算出了应急物资需求量,为灾区的应急物资供应提供科学依据.     

基于ASP．NET的库存管理系统的研究与开发

高效的库存管理是实现企业信息化中的重要环节。以ASP.NET和SQL Server为技术支持,以B/S模式为架构,用软件工程的指导思想开发库存管理系统。实践证明利用该技术开发的基于Web端的企业库存管理系统简单易用,可以很好的提高企业库存管理的工作效率。     

基于库存控制的数据仓库与决策支持

通过对传统决策支持系统已经不能满足当今企业对决策支持的需要的分析,提出了采用数据仓库（DW）,联机分析处理（OLAP）及数据挖掘技术为企业提供决策必要性,设计了一种利用数据仓库（DW）技术和联机分析处理（OLAP）、数据挖掘（DM）等数据仓库工具提供库存控制决策支持的方案,并着重阐述了联机分析处理（OLAP）与数据挖掘是如何为企业库存控制提供决策支持的。     

Online inventory analysis models and system

The purpose of this paper is to report an approach to the development of an online inventory analysis and control system. Attention has been focused on the model aspects of the development process. Inventory Analysis and Control System 1 (IACS 1) is a series of inventory analysis models which is designed to provide management and functional personnel with the analytical tools for inventory decisions on purchasing, production and material control. IACS 1 contains self-explanatory procedures from the selection of a model and definition of the data input to execution of the program and the interpretation of the output result.     

数据仓库在生产连续型企业库存控制中的应用

本文通过对生产连续型企业库存控制的特点分析，指出了仅仅利用传统的基于事务处理的管理信息系统和决策支持系统(DSS)解决该类库存控制决策分析问题的局限性，提出了采用数据仓库技术的必要性，并分析了传统决策支持系统的不足之处以及数据仓库(DW)技术对DSS的支持，设计了一种利用DW技术和数据挖掘(DM)、联机分析处理(OLAP)等
数据仓库工具提供库存控制决策支持的方案。     

Determining critical power equipment inventory using extreme value approach and an auxiliary Poisson model

This paper is devoted to the establishment of reasonable levels of critical power equipment inventory using available historical data and strict legal requirements for reliable electrical power supply. Several models, including an Extreme Value Theory and a Homogeneous Poisson model, are used with results compared to provide a probabilistic formulation of suggested inventory. Several procedures are provided to establish proper inventory levels of critical power equipment. Simplifications are suggested for automating the calculation process for large samples. The presented approaches have a wide scope of industrial applicability, and can be applied to different types of critical equipment. Mathematical background is provided to assist practitioners that do not have extensive knowledge of probabilistic tools such as Extreme Value Theory or Homogeneous Poisson Process models.     

A simulation-optimization approach for integrated sourcing and inventory decisions

In this paper, we study a generalized vendor selection problem that integrates vendor selection and inventory replenishment decisions of a firm. In addition to vendor-specific procurement and management costs, we consider inventory replenishment, holding, and backorder costs explicitly to meet stationary stochastic demand faced by the firm. Our goal is to select the best set of vendors along with the optimum inventory decisions at each plant of the firm so that we minimize the system-wide total costs and achieve desired service and reliability levels. Due to uncertainties inherent in the problem related to demand observed by the firm, quality provided by vendors, and disruptions observed by vendors, we utilize a simulation-optimization approach to solve the problem. More specifically, we build a discrete-event simulation model to evaluate the objective function of the problem that works in concert with a scatter search-based metaheuristic optimization approach to search the solution space. Computational results not only provide managerial insights and measure the significance of intangible factors in the vendor selection process but also highlight the importance of computational tools such as simulation-optimization for the vendor selection problem.     

Exploratory spatio-temporal visualization: an analytical review

Current software tools for visualization of spatio-temporal data, on the one hand, utilize the opportunities provided by modern computer technologies, on the other hand, incorporate the legacy from the conventional cartography. We have considered existing visualization-based techniques for exploratory analysis of spatio-temporal data from two perspectives: (1) what types of spatio-temporal data they are applicable to; (2) what exploratory tasks they can potentially support.The technique investigation has been based on an operational typology of spatio-temporal data and analytical tasks we specially devised for this purpose. The result of the study is a structured inventory of existing exploratory techniques related to the types of data and tasks they are appropriate for. This result is potentially helpful for data analysts—users of geovisualization tools: it provides guidelines for selection of proper exploratory techniques depending on the characteristics of data to analyze and the goals of analysis. At the same time the inventory as well as the suggested typology of tasks could be useful for tool designers and developers of various domain-specific geovisualization applications. The designers can, on the one hand, see what task types are insufficiently supported by the existing tools and direct their creative activities towards filling the gaps, on the other hand, use the techniques described as basic elements for building new, more sophisticated ones. The application developers can, on the one hand, use the task and data typology in the analysis of potential user needs, on the other hand, appropriately select and combine existing tools in order to satisfy these needs.     

Getting started with IT asset management

Asset management is a combination of tools and processes that proactively manage a company's entire asset base from a cost, contractual, support, and inventory viewpoint. This definition stems from the basics of a company's business functions; several common threads lead to a fundamental definition. At the root of business you find a basic equation: assets+people=profits. Since this equation underlies basic business fundamentals, business managers must support each aspect of the equation, and asset management tools and processes must address each area. Companies must possess certain competencies to maximize their effectiveness in each area. Ownership data allows companies to look at their asset base from a strategic business perspective. Help desk and deployment tools remain tactical tools to solve today's problems. Separately or together they do not constitute asset management. To truly manage assets we need all three competencies. Help desks support people and deployment tools support the assets. Ownership management tools support the process by maximizing asset use while lowering the cost of ownership     

A new tool for processing atmospheric emission inventories: Technical aspects and application to the ESCOMPTE study area

Emission databases need to be processed for several purposes, e.g., policy and scientific, and so require flexible and fast handling. As a result, the creation and use of convenient interactive tools allowing easy and fast processing are of high importance. In this paper, a new software devoted to emission inventories processing is presented and applied to the actualization of the ESCOMPTE inventory. The ESCOMPTE inventory is a yearly (1999) high-resolution (1 km²) emission inventory created for use in chemical transport models to study ozone pollution. This tool includes several functions allowing the update of emission inventories at different temporal and spatial resolutions based on the reference ESCOMPTE inventory. The actualized yearly and hourly inventories are found consistent with the hypothesis involved in emission inventory creation. Due to its flexible architecture, several other applications related to air quality analysis can be performed such as the creation of emission scenarios allowing the evaluation of abatement strategies and regulation effects on anthropogenic emissions. Also, the architecture of the software allows an easy application to other emission inventories provided that they have similar or adaptable structure compared to the ESCOMPTE one.     

Diagnostic tools for nearest neighbors techniques when used with satellite imagery

Nearest neighbors techniques are non-parametric approaches to multivariate prediction that are useful for predicting both continuous and categorical forest attribute variables. Although some assumptions underlying nearest neighbor techniques are common to other prediction techniques such as regression, other assumptions are unique to nearest neighbor techniques. Graphical diagnostic tools are proposed to evaluate the assumptions and to address issues of bias, homoscedasticity, influential observations, outliers, and extrapolations. The tools are illustrated using results obtained from applying the k-Nearest Neighbors technique with Landsat imagery and forest inventory ground observations.