通过在地图上或GUI网络图的节点上点击，网络操作中心工作人员可以监控任何特定设备的状态并更改其设置和配置。
By clicking on a map or a node of a GUI network graph, the network operations center staff could monitor the status of any particular device and change its setting and configurations.
多层前馈人工神经网络在装备故障诊断中的应用含设备运行状态特征值设定和故障判定。
The application of multi-layer feed-forward artificial neural network in fault equipment diagnosis includes feature value setting of equipment operation condition and fault judgment.
TCP的目标就是确保网络中的每一台设备都是合作状态，而不会压跨它占有的资源。
The purpose of TCP Congestion Control was to ensure that every device on the network cooperates to not overwhelm its resource.
策略决策点PDP了解网络设备的状态，能配置和修改设备中的策略。
PDP know the state of the network devices and can configure and rectify the policies in the devices.
系统采用设备驱动程序编程构造状态检测模块；网络驱动程序通过NDIS程序库对调用硬件系统。
The state inspection module was built up with device driven programming, hardware system is called by using network driven program with NDIS library.
使用SNMP协议网络管理员能够从远程捕获和监控网络系统设备(如网络交换机和路由器等)的工作情况和状态。
With SNMP protocol, network manager can remotely capture and monitor the operation condition and states of network system units (such as network exchanger and router, etc).
介绍了设备状态检修专家系统的结构，提出了一种基于模块化的神经网络的系统结构和学习算法。
This article introduces the structure of condition-based maintenance expert system, and a structure and algorithm about modular neural network is proposed.
使用颜色编码的LED基于网络延迟和设备可用性，设备的状态描述。
The status of devices is depicted using color coded LEDs based on network latency and device availability.
利用人工神经网络理论，通过对设备振动信号采集、处理和提取特征参数的方法，对装载机机械系统工作状态进行智能监测与故障诊断。
This paper involves ANN based intelligent condition monitoring and diagnosing of loaders, focusing on signal collecting and processing as well as characteristic parameter picking up.
它采用先进的现场总线、传感器、计算机网络技术，利用数据库等软件工程，对现场信号设备实施动态监测，状态信息储存、重放和报警等。
It realizes the dynamic monitoring, condition information memory, re-play and warning etc. to the spot signal devices by use of the advanced spot bus, sensors, web techniques, data base.
本课题创建了设备状态监测无线网络平台，在此平台上研究对设备状态得监测技术。
In the project we created the platform for equipment status monitor, with which we research the technology for monitor equipment status.
提出了设备运行状态综合预测模型，神经网络和灰色理论的组合应用，提高了状态预测的准确性。
A synthetic condition prediction model is presented, using neural network and grey theory together make it possible to predict accurately.
该系统采用产生式知识表示法和框架知识表示法，通过在数据库中分别建立规则库、状态库、网络拓扑知识库和设备属性库来完整表述变电站的全部信息。
Knowledge production and frame representation are used to build rule database, status database, topology database and property database, these databases can describe all information of a substation.
DNC状态监控系统已成为实现制造企业生产信息集成和网络制造设备层远程诊断的关键技术。
State monitoring system for DNC has become the key technology in realizing manufacture information integration for manufacture enterprises and remote diagnosis for networked manufacture equipments.
本文介绍的网络管理平台采用SNMP标准对网络设备进行管理，并且通过实时图像直观的对设备状态进行显示和告警。
The introduced network operation monitoring system uses SNMP standards for the management of network equipment, and use real-time image to display network equipment status.
并采用了基于可靠性理论的故障树思想对设备故障情况进行分析和判断，在设备状态检修的方式方法上采用了BP神经网络进行设备的故障状态诊断。
And based on the reliability theory, we use the fault tree to analyse and determine the equipment condition, and use BP neural network to diagnose equipment in condition-based maintenance.
SNMP监控与分析企业的网络情况，实施安全策略，实时监控网络设备、服务器等，保证网络的运行状态和性能。
SNMP network monitoring analysis of business conditions, the implementation of security policy, real-time monitoring network devices, servers, etc., to ensure network operations performance.
SNMP监控与分析企业的网络情况，实施安全策略，实时监控网络设备、服务器等，保证网络的运行状态和性能。
SNMP network monitoring analysis of business conditions, the implementation of security policy, real-time monitoring network devices, servers, etc., to ensure network operations performance.
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