一种信息系统的评价模型及其实现

将信息系统的评价指标体系进行分层，得到参与评价的三维指标矩阵，再将多目标决策中的逼近理想解法应用到以矩阵为元素的空间中，按照与理想解和负理想解的相对接近度去对信息系统作出综合评价，据此提出一种新的信息系统评价模型，讨论了模型的主要实现技术，并给出了一个信息系统评价实例。     

基于博弈论和云模型的通用机场选址方案评价

为了解决通用机场选址方案的最优化决策问题,以及决策过程中指标的多样性和不确定性,给出了一个评价方案.首先,确定了6个一级指标和22个二级指标,构建了较为全面的通用机场选址方案评价指标体系;其次,结合通用机场选址方案指标特性,利用G1法和熵权法对评价指标进行赋权,并采用博弈论确定了指标的最优化综合权重;再次,搭建了适用于...     

Matlab在防护工程伪装效果评价中的应用

针对防护工程伪装效果优劣问题,给出了一种利用matlab来评价防护工程伪装效果的方法。通过分析防护工程伪装效果评价的总体架构,分别利用matlab的图像处理工具箱、统计学工具箱以及矩阵运算功能建立相关模块。实现了遥感数字图像处理、层次聚类构建指标体系、AHP确定指标权重和灰色聚类评价功能。最后通过一个实例证实运用该方法能较好满足防护工程口部伪装效果评价的需求。     

体育电子政务平台软件方案理想解评价方法

建设体育电子政务平台是各级体育主管部门进行体育资源优化配置、拓展体育信息资源的开发利用以及提高体育事业发展水平的重要内容。针对平台软件方案难以选择的问题，文中运用理想解法对多个方案进行综合评价。首先，根据以前的研究成果简要说明了评价指标体系及权重；然后，构建理想解评价方法的数学模型，包括原始评价矩阵、定性指标定量化、无量纲化处理、加权评价矩阵、欧氏距离等方面；最后，按照理想解法的评价步骤给出了综合评价实例。运用文中的研究内容进行体育电子政务平台软件方案综合评价，可得出良好的可比性评价排序结果。     

综合评价法在乳制品物流配送中心选址问题中的研究

乳业物流配送中心的选址对于构建乳品物流网络、降低物流成本、提高乳制品物流企业的效益有着重要意义,本文利用综合评价法对影响乳业物流配送的各影响因素进行分析、计算,选取可达到配送中心整体最优的效果方案,对乳业物流配送选址问题有一定的显示参考意义.     

DIS作战指挥辅助决策系统的实现

文章首先提出了DIS作战指挥系统中辅助决策子系统的方案,然后给出系统的设计思想、软硬件方案,并讨论了关键技术。     

军队指挥自动化系统信息安全防护探讨

该文基于军队指挥自动化系统的概念及其地位,结合指挥自动化系统的结构及其作用,分析了信息安全威胁的方式,并从完善信息安全保密机制、加强反电子干扰、注重网络防护等方面提出了信息安全防护的措施。     

基于工作流的指挥决策系统模型研究

针对传统的指挥决策系统自动化程度不高等问题,提出了基于工作流的指挥决策系统模型。该模型由工作流元模型演化而来,将指挥决策的共性流程划分为若干个关键业务活动，通过一定规则前后进行关联,每个活动又可以根据实际特点划分为子活动，有效地利用了工作流思想提高了系统的自动化程度。基于该模型开发了一个指挥决策原型系统，该原型系统参照工作流管理系统设计方法，采用C/S体系架构，通过调度服务器任务指令自动控制客户端的活动。经定性分析，该模型相对于传统的设计方法具有通用性、可靠性、智能性等优点。     

基于WebGIS的震后重建决策选址模型研究

地震后的城镇重建工作异常艰巨和复杂,选址是城镇重建工作中最重要的长期规划.为了让选址决策更加科学有效,将WebGIS与决策支持系统有机地集成起来,构成空间决策支持系统.即借助GIS对空间数据的编辑、存储、管理、查询、分析和显示等功能,在决策支持系统中加入空间分析模块,使之能够辅助决策者求解复杂的选址决策问题.     

物流中心选址的神经网络集成模型研究

针对在建立物流中心选址模型中,单个人工神经网络模型难以确定参数、容易产生“过拟合”等问题,提出一种神经网络二次集成模型,利用Bootstrap可重复采样技术得到不同的训练集来训练产生不同的个体神经网络,采用粒子群优化算法结合个体输出获得神经网络集成,并在此基础上将集成视为个体再次结合。实验结果表明,该模型易于设计且能够提高泛化能力。     

用于版权保护的图像数字水印方案

指出和论述了现有私有水印方案在版权保护方面存在的重要缺陷——不能防止伪造攻击;提出一个旨在防止伪造攻击的水印方案,并从理论上论证了其安全性。实验证明该方案具有可行性、鲁棒性和安全性。     

Rational model selection in large engineering knowledge bases

It is generally admitted that several models differing along various dimensions are needed for executing complex engineering tasks such as diagnosis and monitoring. A key problem is thus to decide what model to use in a particular situation in front of a specified problem-solving task and reasoning objectives. We address this problem within the Multimodeling framework for reasoning about physical systems that we proposed in a previous work. After having characterized the space of possible models in the Multimodeling approach, we formulate the selection problem using the conceptual tools offered by the economic theory of rationality. In this frame we illustrate a preference-based model selection method that is used to navigate in the universe of available models of a system searching for the model that best matches a given task and reasoning objectives. The method exploits the use of a model map that is a metalevel concept representing the ontology and teleology of each model and the transformational relations (abstractions and approximations) connecting each model to other models. The model map is used to compare models on the basis of their content and to understand what can be gained or lost when switching from one model to another. Finally, some implications of the foregoing selection method in developing action-based diagnostic systems are discussed.     

A deterministic model selection scheme for incremental RBFNN construction in time series forecasting

This paper presents a fast and new deterministic model selection methodology for incremental radial basis function neural network (RBFNN) construction in time series prediction problems. The development of such special designed methodology is motivated by the problems that arise when using a K-fold cross-validation-based model selection methodology for this paradigm: its random nature and the subjective decision for a proper value of K, resulting in large bias for low values and high variance and computational cost for high values. Taking into account these drawbacks, the proposed model selection approach is a combined algorithm that takes advantage of two balanced and representative training and validation sets for their use in RBFNN initialization, optimization and network model evaluation. This way, the model prediction accuracy is improved, getting small variance and bias, reducing the computation time spent in selecting the model and avoiding random and computationally expensive model selection methodologies based on K-fold cross-validation procedures.     

等级OSPF网的安全保护方案

开放式最短路径优先(OSPF)协议作为目前大规模网络应用最广泛的自治域内路由协议,其安全不仅仅关系到自治域内,同时也关系到自治域外乃至整个网络的正常运行。传统的基于非对称性加密算法的数字签名解决方案能够实现端到端的安全验证,但是却忽略了点对点的方式,而且存储量和额外开销也一直是急需解决的问题。基于对称性加密算法,提出了适宜于OSPF等级区域的安全防护方案HS-OSPF。HS-OSPF扩充了OSPF网原有的二层等级结构,设计了合理、高效的密钥分配与管理方案,克服了传统非对称性密码方案的不足,降低了密钥存储量和系统开销,提高了网内安全通信的实时性。     

An evidence-based scheme for web service selection

Existing studies on the web service selection problem focus mainly on the functional QoS properties of the service rather than the consumer satisfaction and trust aspects. While a good QoS enhances the reputation of a service, different consumers invariably hold differing views of the service contents. Some service reputation approaches primarily consider the consumer’s prior experience of the service via opinion feedback system, may neglect the effect of social trust transition in the recommendations of others. As a result, the problem of reaching consensus on the level of consumer trust regarding service becomes one of key issues in service selection. This study proposes a trust-based service selection model to estimate the degree of consumer trust in a particular service based on the consumers’ direct experience and indirect recommendation of the service. In the proposed approach, the degree of consumer trust is correctly estimated by extending Dempster–Shafer evidence reasoning theory to the reputation computation using consumers’ direct experience and incorporating Jøsang’s belief model for solving the trust transition problem in the indirect recommendation of the service. The proposed model effectively enables deception detection by means of existing bodies of evidence, and therefore excludes the fraudulent evidence of malicious evaluators from the selection process. In addition, a quality index is proposed to help third party (TTP) examine the body of evidence and make the outranking result more reliable. Importantly, the quality index is based not only on the confidence degree of the evidence, but also on the support degree, and therefore discovers the effects of intentional negative assessments. The validity of the proposed approach is demonstrated numerically by means of two service selection examples.     

僵尸网络命令与控制信道的特征提取模型研究

僵尸网络发起的分布式拒绝服务攻击、垃圾邮件发送以及敏感信息窃取等恶意活动已经成为网络安全面临的重要威胁。命令与控制信道正是僵尸网络操纵这些恶意活动的唯一途径。利用命令与控制信道中攻击命令具有相对固定的格式和命令字的特点,基于现有的特征提取技术,针对边缘网络的可疑流量,提出了一个新型的特征提取模型。实验结果表明,该模型能够准确地提取出具有命令格式的特征,而且由这些特征转化的入侵检测规则能够有效识别感染的僵尸主机。     

基于面向服务架构的调度命令系统模型开发研究

首先介绍了面向服务的架构(SOA)的体系结构和有色Petri网的概念;然后,使用SOA的方法,通过对调度命令系统业务流程的梳理,提取出调度命令系统的一组服务模型,形成服务总线模式的调度命令系统的SOA架构;最后,以调用下达命令服务为例,将系统拆分为服务提供者、服务请求者和服务总线三个组件,再将服务总线组件拆分为接入访问组件、权限认证组件、服务路由组件和消息转换组件,利用有色Petri网在动态建模方面的优势,分别对其进行建模,详细说明了其内部流程.SOA架构提高了调度命令系统的灵活性和可扩展性,结合有色Petri网对系统内部结构和控制逻辑的形式化描述,这种架构方法与建模语言相结合的方法对调度命令系统的开发有一定的指导意义.