Research and Design of IPv6 Network Management and Operations Support System

IPv6 is the foundation of the development of Next Generation Internet (NGI). An IPv6 network management and operations support system is necessary for real operable NGI. Presently there are no approved standards yet and relevant equipment interfaces are not perfect. A Network Management System (NMS) at the network layer helps implement the integrated management of a network with equipment from multiple vendors, including the network resources and topology, end-to-end network performance, network failures and customer Service Level Agreement (SLA) management. Though the NMS will finally realize pure IPv6 network management, it must be accommodated to the management of relevant IPv4 equipment. Therefore, modularized and layered structure is adopted for the NMS in order to implement its smooth transition.

Decision Support System for Maintenance Management Using Bayesian Networks

The maintenance process has undergone several major developments that have led to proactive considerations and the transformation fiom the traditional ＂fail and fix＂ practice into the ＂predict and prevent＂ proactive maintenance methodology. The anticipation action, which characterizes this proactive maintenance strategy is mainly based on monitoring, diagnosis, prognosis and decision-making modules. Oil monitoring is a key component of a successful condition monitoring program. It can be used as a proactive tool to identify the wear modes of rubbing pans and diagnoses the faults in machinery. But diagnosis relying on oil analysis technology must deal with uncertain knowledge and fuzzy input data. Besides other methods, Bayesian Networks have been extensively applied to fault diagnosis with the advantages of uncertainty inference; however, in the area of oil monitoring, it is a new field. This paper presents an integrated Bayesian network based decision support for maintenance of diesel engines.

One-pot synthesis of network supported catalyst using supramolecular gel as template

A simple and general strategy is described for preparing network supported catalyst through a one-pot synthetic procedure using supramolecular gel as template.This procedure directly attaches ligand to support during fabricating the support.Using this strategy,supported CuBr/di-（2-picolyl） amine catalyst with U-shaped fibrillar network was prepared and used in atom transfer radical polymerization of methyl methacrylate.XPS and SEM characterization of the catalyst revealed homogeneous distribution of ligand,sufficient reactive sites,adequate mechanical strength and macroporosity.The polymerization results demonstrated high activity and reusability of such catalyst.This strategy might be extended to other supported catalysts used in column reactors.

XML-based Data Processing in Network Supported Collaborative Design

In the course of network supported collaborative design, the data processing plays a very vital role. Much effort has been spent in this area, and many kinds of approaches have been proposed. Based on the correlative materials, this paper presents extensible markup language （XML） based strategy for several important problems of data processing in network supported collaborative design, such as the representation of standard for the exchange of product model data （STEP） with XML in the product information expression and the management of XML documents using relational database. The paper gives a detailed exposition on how to clarify the mapping between XML structure and the relationship database structure and how XML-QL queries can be translated into structured query language （SQL） queries. Finally, the structure of data processing system based on XML is presented.

Design of Distributed Authentication Mechanism for Equipment Support Information Network

Considering the secure authentication problem for equipment support information network,a clustering method based on the business information flow is proposed. Based on the proposed method,a cluster-based distributed authentication mechanism and an optimal design method for distributed certificate authority( CA)are designed. Compared with some conventional clustering methods for network,the proposed clustering method considers the business information flow of the network and the task of the network nodes,which can decrease the communication spending between the clusters and improve the network efficiency effectively. The identity authentication protocols between the nodes in the same cluster and in different clusters are designed. From the perspective of the security of network and the availability of distributed authentication service,the definition of the secure service success rate of distributed CA is given and it is taken as the aim of the optimal design for distributed CA. The efficiency of providing the distributed certificate service successfully by the distributed CA is taken as the constraint condition of the optimal design for distributed CA. The determination method for the optimal value of the threshold is investigated. The proposed method can provide references for the optimal design for distributed CA.

Collaborative Filtering and Artificial Neural Network Based Recommendation System for Advanced Applications

To make recommendation on items from the user for historical user rating several intelligent systems are using. The most common method is Recommendation systems. The main areas which play major roles are social networking, digital marketing, online shopping and E-commerce. Recommender system consists of several techniques for recommendations. Here we used the well known approach named as Collaborative filtering (CF). There are two types of problems mainly available with collaborative filtering. They are complete cold start (CCS) problem and incomplete cold start (ICS) problem. The authors proposed three novel methods such as collaborative filtering, and artificial neural networks and at last support vector machine to resolve CCS as well ICS problems. Based on the specific deep neural network SADE we can be able to remove the characteristics of products. By using sequential active of users and product characteristics we have the capability to adapt the cold start product ratings with the applications of the state of the art CF model, time SVD++. The proposed system consists of Netflix rating dataset which is used to perform the baseline techniques for rating prediction of cold start items. The calculation of two proposed recommendation techniques is compared on ICS items, and it is proved that it will be adaptable method. The proposed method can be able to transfer the products since cold start transfers to non-cold start status. Artificial Neural Network (ANN) is employed here to extract the item content features. One of the user preferences such as temporal dynamics is used to obtain the contented characteristics into predictions to overcome those problems. For the process of classification we have used linear support vector machine classifiers to receive the better performance when compared with the earlier methods.

IS YOUR NETWORK SUPPORTING YOUR TERMINALS? OR IS IT THE OTHER WAY AROUND?

Both, actually. That’s why ZTE provides not only network solutions, but also terminals that work as integral parts of

IS YOUR NETWORK SUPPORTING YOUR TERMINALS? OR IS IT THE OTHER WAY AROUND?

Both,actually.That’s why ZTE provides not only network solutions,but also terminals that work as integral parts of optimised systems.

IS YOUR NETWORK SUPPORTING YOUR TERMINALS? OR IS IT THE OTHER WAY AROUND?

Both,actually.That’s why ZTE provides not only network solutions,but also terminals that work as integral parts of optimised systems.

Wireless Network Technologies Supporting M2M Applications

When computers and communication devices are available everywhere in the future, the categories of communication will expand to cover not only the man-man and the man-machine, but also the machine-machine (M2M) communication. Someday, the traffic generated by machines will greatly exceed those of man-machine and man-man applications. Large numbers of M2M applications will need various wireless networks to support them. This paper introduces the characteristics, advantages and disadvantages of the currently available various wireless network technologies, including WiFi, Bluetooth, ZigBee, passive RFID and the 802.15 standard networks.

AN INTELLIGENT DECISION SUPPORT SYSTEM （IDSS） IN THE OPERATION PROCESS OF ELECTRIC FURNACE FOR CLEANING SLAG

In this paper, the structure and function of the IDSS in the operation process of electric furnace for cleaning slag are presented and the fuzzy neural network decision model (FNNDM) in the IDSS is specially suggested. The IDSS possesses selflearning and adaptive properties, and has been used for managing and analyzing the optimal operational conditions since June 1992. Electric energy consumption has been reduced remarkably and the coefficient of recovery of cobalt and nickel has been increased.

Intelligent Decision Support System for Bank Loans Risk Classification

Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.

大型医院医疗物资保障系统韧性评价

为有效评价大型医院医疗物资保障系统抵御突发事件干扰并快速恢复的能力,需要引入韧性概念。本文提出利用动态贝叶斯网络对大型医院的医疗物资保障系统进行韧性评价。首先,筛选出影响系统韧性的因素;其次,引入时间维度,利用动态贝叶斯网络建立韧性评价模型,采用专家打分法量化节点概率,并结合Leaky Noisy-or gate模型修正计算条件概率。随后,利用动态贝叶斯网络的双向推理功能对系统的韧性进行评价。最后,选取案例验证该评价模型的可行性和实用性。通过正向分析,得到了系统韧性的时序变化曲线和最大致因链,通过逆向推理得到影响系统韧性的5个关键因素。结果表明,动态贝叶斯网络能够有效评价大型医院医疗物资保障系统韧性,为有效提高医院医疗物资保障系统韧性提供有效思路。

基于多层耦合网络的装备保障体系级联失效及抗毁性分析

为准确描述装备保障体系结构特征与毁伤失效流程,进而提升装备保障体系功能与抗毁能力,基于杀伤层、保障层和储供层构建装备保障体系的多层耦合网络模型。基于杀伤链给出装备维修保障链与储供保障链的特征和典型样式,在此基础上,提出考虑装备保障体系多层耦合网络特性的级联失效模型与节点重要度评估方法。给出对应的网络抗毁性评估指标。仿真结果表明,考虑级联失效的多层耦合网络模型能较好地反映遭受攻击时整个装备保障体系的性能变化情况,所提出的使命任务节点重要度能准确识别关键节点。与传统网络抗毁性指标相比,杀伤链数量对节点失效产生的装备保障体系抗毁性变化更加敏感。

基于EMI-CNN的建筑施工模板支撑体系节点健康监测

为预防模板坍塌引发建筑施工安全事故风险,提出一种基于压电阻抗法(EMI)和卷积神经网络(CNN)的模板支撑体系节点智能监测方法。首先,利用压电陶瓷传感器(PZT)的机电耦合特性及其集驱动-传感于一体的特点,建立PZT-节点耦合系统的机电阻抗传感机制模型;其次,基于EMI法,以与待测结构耦合的PZT片电导信号为监测指标,确定模板支撑体系节点松动的发生;然后,以敏感频段内PZT片的801个原始电导信号为模型输入,9个节点松动程度为模型输出,构建162组学习样本和27组测试样本,建立EMI-CNN模型,确定节点松动程度;最后,以一个实际工程中的建筑施工模板体系节点为例,验证EMI-CNN模型的有效性,并对比分析EMI-BP模型。研究结果表明:EMI-CNN模型经过85次迭代达到收敛,预测准确率达到100%,相较于EMI-BP模型提高29.63%。该监测方法可实现对建筑施工模板支撑体系节点健康状态实时、准确、无损监测。

基于自智网络的网络运营支撑系统智能化演进

网络运营支撑系统(OSS)是当前运营商通信网络数智转型的重要抓手,参考TM Forum的自智网络方法,结合IT领域的中台理念,通过业务和技术2个层面双轮驱动,以数字化转型和智能化提升为主要方向,确定集约的“平台+应用”OSS目标架构,分阶段整合原有分散的烟囱系统,推动网络智慧运营从信息化走向数字化、从自动化走向智能化,在实践中践行“数智强企”发展理念。

基于模糊神经网络PID的煤矿掘进机俯仰控制研究

目前煤矿掘进机俯仰控制主要采用PID控制方法,在掘进机俯仰控制时变性与液压系统非线性情况下的控制精度不高。掘进机俯仰控制通过控制液压缸行程实现,将传统PID算法与模糊控制、神经网络等相结合,可有效提高液压缸行程控制精度。提出了一种基于模糊神经网络PID的煤矿掘进机俯仰控制方法。通过分析掘进机支撑部运动学关系,得到俯仰角与支撑部液压缸的数学关系;介绍了掘进机俯仰控制液压系统工作原理,建立了液压系统及其传递函数模型;将模糊控制与神经网络相结合,形成模糊神经网络,利用模糊神经网络优化PID控制参数,再结合支撑机构数学模型和液压系统传递函数模型,建立掘进机俯仰角模糊神经网络PID控制模型,实现煤矿掘进机俯仰机构自动精确控制。该方法可使掘进机俯仰机构更加快速、准确到达预设位置,解决掘进机俯仰控制中的时变性与非线性难题。仿真结果表明:模糊神经网络PID控制算法相较于模糊PID和PID控制算法,跟踪误差分别降低了69.34%和74.49%。通过液压缸位移控制模拟煤矿掘进机在突变工况和跟随工况下的俯仰控制,结果表明:模糊神经网络PID控制算法相比模糊PID和PID控制算法,俯仰控制跟踪误差最小,对位置信号的平均响应时间分别缩短了27.22%和50.33%,动态控制性能更好。

Linked Data Based Framework for Tourism Decision Support System: Case Study of Chinese Tourists in Switzerland

Switzerland is one of the most desirable European destinations for Chinese tourists;therefore, a better understanding of Chinese tourists is essential for successful business practices. In China, the largest and leading social media platform—Sina Weibo, a hybrid of Twitter and Facebook—has more than 600 million users. Weibo’s great market penetration suggests that tourism operators and markets need to understand how to build effective and sustainable communications on Chinese social media platforms. In order to offer a better decision support platform to tourism destination managers as well as Chinese tourists, we proposed a framework using linked data on Sina Weibo. Linked Data is a term referring to using the Internet to connect related data. We will show how it can be used and how ontology can be designed to include the users’ context (e.g., GPS locations). Our framework will provide a good theoretical foundation for further understand Chinese tourists’ expectation, experiences, behaviors and new trends in Switzerland.

天基信息支援体系建模与效能评估方法

针对天基信息支援体系效能评估中存在的主观性强与复杂性高的问题,提出一种基于投影梯度神经网络的天基信息支援体系效能评估方法。首先,基于国防部体系框架(Department of Defense Architecture Framework,DoDAF)视图产品与包以德循环(observation,orientation,decision,action,OODA)梳理体系作战流程,进而建立评估指标体系,并基于离散事件仿真生成效能评估数据样本。然后,基于Rosen-反向传播(back propagation,BP)神经网络构建效能评估代理模型,并通过对权重参数的限制来解决在效益型指标下评估模型难以解释的问题。最后,对仿真样本进行评估模型验证试验,结果表明所提方法在天基信息支援体系效能评估中相较于传统BP神经网络计算性能提升超过50%,能够为天基信息支援体系效能评估提供技术支撑。