网络故障框架提供给开发人员一个API，此 API 可以分类由应用程序传递给它的网络异常。
The network faults framework provides developers with an API that categorizes network exceptions passed to it by an application.
将支持向量机应用于网络入侵检测，提出一种基于支持向量机的网络异常入侵检测模型。
Apply SVM technique to network intrusion detection, and propose a network abnormal intrusion detection model based on SVM.
基于对真实网络流量数据的观察，在突发异常的定义中引入持续性因子及突变性因子，以更好地描述其在真实应用环境中的特征。
Based on the observation of real network traffic data, we introduce the lasting factor and abrupt factor in the definition of burst in order to better characterize the burst in the real application.
在网络异常入侵检测中，应用基于QPSO的WLS - SVM算法效果显著，特别是对于小样本数据量具有良好的预测能力。
In the web anomaly intrusion detection, the application of the WLS-SVM based on QPSO algorithm, the results is significantly, especially to small sample size of data has good predictive ability.
若要响应用户错误和运行时错误条件(例如网络错误或权限失败)，应引发一个异常。
To respond to user errors and to run-time error conditions such as network errors or permission failures, throw an exception.
若要响应用户错误和运行时条件（例如网络错误或权限失败），请引发异常。
To respond to user errors and run-time conditions such as network errors or permissions failures, throw an exception.
最后，通过自适应边界值方法进行检测，能够及时发现异常流量行为，说明该模型应用于网络流量预测是可行、有效的。
Finally, abnormal behaviors of network traffic can be found on time through test of adaptive boundary value method, which proves that the model is feasible and effective.
本文随后提出了一种适合于无线传感器网络中异常事件监测应用的环状空间相关性模型。
This paper proposes a circular spatial correlation model, which is more suitable for the application of WSN in anomaly detection.
本文随后提出了一种适合于无线传感器网络中异常事件监测应用的环状空间相关性模型。
This paper proposes a circular spatial correlation model, which is more suitable for the application of WSN in anomaly detection.
应用推荐