远程主机，指的是识别你正在使用的电脑网络位置的IP地址或者域名。
The remote host is the IP address or domain name that identifies the location of the computer network you are using.
网络识别位置抽象能进行快速和轻松的灾难恢复。
ion of location from network identity which allows for quick and easy disaster recovery.
基于IP的位置识别利用了用户的网络信息，包括子网、网络掩码和路由器的mac地址。
IP-based location awareness USES the user's network information, including subnet, net mask, and the Mac address of the router.
基于遗传神经网络与模态应变能，提出了一种斜裂缝两阶段诊断方法，识别梁体中斜裂缝的位置、角度和深度。
Based on genetic neural network and modal strain energy, a two-stage method for detecting diagonal cracks is proposed to identify the location, Angle and depth of diagonal cracks in beams.
本文研究了简单背景下，发生尺度、角度、位置变化的目标的神经网络识别、定位方法。
The dissertation is the study of the target recognition and orientation which has change of Angle, translation and scale under the simple background, based on the neural networks.
模型修正后，本文基于神经网络的多重分步识别方法，对斜支撑进行位置及截面刚度的识别。
After updating the model, this paper carried out the experiment of identifying the position and section stiffness of steel support based on the neural network multi-step identification method.
发现基于概率神经网络的结构损伤定位方法能够正确识别单一位置损伤，且组合参数作为输入指标时的识别效果更好。
The result indicates that probabilistic neural networks can localize the single damage correctly, and the networks with the compounded index show better effectiveness.
通过对一个悬臂仿梁建立仿真模型，运用BP神经网络对其进行损伤位置识别，结果表明，BP神经网络对单一损伤位置识别效果很好。
A cantilever beam model is established by simulation. And using BP neural network identify the damage location. The results reveal that the BP neural network for single damage identification.
您的位置信息是基于细胞身份证定位，即通过蜂窝网络识别你的设备的位置。
Your location information is based on cell ID positioning, that is, the cellular network recognises the location of your device.
位置的确定采用PNN神经网络，截面刚度的识别采用RBF神经网络。
Here used the PNN neural network to determine the position and RBF neural network identify the section stiffness of steel supports.
数值模拟结果表明 ，采用本文提出的损伤指标、采用神经网络方法 ，分两阶段进行青马大桥桥板结构的损伤位置识别是有可能的。
In the second stage, the artificial neural network is used to identify damaged member in a damaged segment. The results show that the pro…
研究表明改进的BP神经网络可用于识别桥梁结构损伤位置和损伤程度；
The result indicates the Improved BP network can detect not only the damage position but the damage degree;
研究表明改进的BP神经网络可用于识别桥梁结构损伤位置和损伤程度；
The result indicates the Improved BP network can detect not only the damage position but the damage degree;
应用推荐