What is the translation of " ANOMALY DETECTION " in Chinese?

• 异常检测

Examples of using Anomaly detection in English and their translations into Chinese

It is likewise called as anomaly detection.
也称为异常侦测。

Anomaly detection and various protection functions during the charging process ensure safety and reliability.
充电过程的异常检测和各种保护功能可确保安全性和可靠性。

Throw away minority examples and switch to an anomaly detection framework.
舍弃所有少数类，切换成一个异常检测框架。

They could be used in anomaly detection, or they could be used to build more general sorts of predictive models.
它们可以用于异常检测，或者用来打造更通用的预测模型。

Azure Stream Analytics- Machine learning- based anomaly detection functions.
Azure流分析-基于机器学习的异常情况检测功能.

Anomaly detection can help find terrorists, clandestine agents, or indications and warning of potential enemy military activity.
通过异常检测可以帮助找到恐怖分子，秘密特工，或潜在的敌人军事活动的迹象和警告。

This book begins with an explanation of what anomaly detection is, what it is used for, and its importance.
这本书首先解释了异常检测是什么，它的用途和重要性。

You may also want to monitor the input data and react to abnormal data(e.g., using an anomaly detection algorithm).
你可能还要监测输入数据，对反常数据做出反应（比如，使用异常检测算法）。

Anomaly detection powered by predictive models and machine learning is used by financial organizations to detect fraudulent transactions.
在预测模型和机器学习基础上的异常检测被金融组织用于检测欺诈性交易。

NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources.
NuPIC适合于各种各样的问题,尤其是检测异常和预测的流数据来源。

Many types of machine learning problems require time series analysis, including classification, clustering, forecasting, and anomaly detection.
很多类型的机器学习问题都需要时间序列分析，其中包括分类、聚类、预测和异常检测。

In the next 12 months, respondents plan to implement industrial anomaly detection tools(42%) and security awareness training for staff.
在未来12个月，参与调查的企业计划部署工业异常检测工具（42％）和员工安全意识培训。

AI's anomaly detection and pattern recognition capabilities could help a system learn from the unstructured data collected by financial institutions.
AI的异常检测和模式识别功能可以帮助系统从金融机构收集非结构化数据。

You may also want to monitor the input data and react to abnormal data(e.g., using an anomaly detection algorithm).
您可能还需要监视输入数据并对异常数据作出反应（例如，使用异常检测算法）。

Combining AI anomaly detection with systems set up by humans to distinguish good and bad actions appears to offer the best of both techniques.
将人工智能异常检测与人类建立的系统相结合，以区分好的和坏的行为，似乎提供了这两种技术的最佳效果。

These tools can range from simple operations to more complex mathematical calculations, including regression algorithms, forecasting, or anomaly detection.
这些工具的范围从简单的操作到更复杂的数学计算，包括回归算法，预测或异常检测。

After the Statsbot team published the post about time series anomaly detection, many readers asked us to tell them about the support vector machines approach.
在Statsbot团队发布关于时间序列异常检测的帖子之后，许多读者要求我们向他们介绍支持向量机的方法。

In mid-2008, the Naval Air Systems Command(NAVAIR) deleted the requirement for the P-8A to be equipped with magnetic anomaly detection(MAD) equipment.
年中期，海军航空系统司令部（NAVAIR）去除关于P-8A将配备磁异常检测（MAD）设备要求。

Once a baseline is established, AI can use anomaly detection and other features to avoid many common problems, such as DHCP, RADIUS, and security problems.
一旦确定了基线，AI就可以使用异常检测和其他特性来避免许多常见的问题，比如DHCP、RADIUS和安全问题。

And most of the data that are used- for example, in manufacturing automation systems on factory floors- are utilized only for real-time control or anomaly detection.
而大多数被使用的数据――例如，工厂车间的自动化系统――只用于实时控制或异常检测。

As of April 12, 2018, the Anomaly Detection feature has been removed from Reports& Analytics and is available exclusively in Analysis Workspace.
自2018年4月12日起，异常检测功能已从Reports&Analytics中删除，并且只能在AnalysisWorkspace中使用。

The solution leverages both supervised learning techniques, such as the classification of suspicious transactions, and unsupervised learning, e.g. anomaly detection.
这个解决方案利用了有监督的学习技术，如可疑交易的分类，以及非监督学习，如异常检测。

NASA uses a machine-learning tool called Amazon SageMaker to train an anomaly detection model using the built-in AWS Random Cut Forest algorithm.
NASA使用一种称为AmazonSageMaker的机器学习工具来使用内置的AWSRandomCutForest算法训练异常检测模型。

The most relevant types of machine-learning algorithms for cognitive IoT apps are forecasting, including time-series forecasting, anomaly detection, and optimization.
对于认知IoT应用程序而言，最相关的机器学习算法类型是预测，包括时序预测、异常检测和优化。

To tackle security issues, for instance, predictive analytics can use anomaly detection algorithms to sniff out suspicious activities and identify possible data breaches.
例如，为了解决安全问题，预测分析可以使用异常检测算法来发现可疑活动，并识别可能的数据泄露。

Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks.
本书使用Python中的Keras和PyTorch，重点介绍如何将各种深度学习模型应用于半监督和非监督异常检测任务。

The system finds its uses in model generation for fraud, risk and anomaly detection, geo-analytics and cyber security, real-time fleet management and incentive-based insurance.
该系统可用于模型生成中的欺诈、风险和异常检测，地理分析和网络安全，实时车队管理和激励型保险。

It can be widely used in anomaly detection, Bayesian networks, CARMA, Cox regression and basic neural networks that use multilayer perceptron with back-propagation learning.
它可广泛用于异常检测、贝叶斯网络、CARMA、Cox回归以及使用多层感知器和反向传播学习的基本神经网络。

It can be extensively applied in Bayesian networks, anomaly detection, CARMA, Cox regression and basic neural networks that utilise multilayer perceptron with back-propagation learning.
它可广泛用于异常检测、贝叶斯网络、CARMA、Cox回归以及使用多层感知器和反向传播学习的基本神经网络。

It can also be used for anomaly detection, Bayesian networks, CARMA, Cox regression and basic neural networks that use multilayer perceptron with back-propagation learning.
它也可以用于异常检测、贝叶斯网络、carma、cox回归以及使用多层感知器进行反向传播学习的基本神经网络。