Towards a deep learning-based outlier detection approach in the context of streaming data
Uncommon observations that significantly vary from the norm are referred to as outliers.
Outlier detection, which aims to detect unexpected behavior, is a critical topic that has …
Outlier detection, which aims to detect unexpected behavior, is a critical topic that has …
Entropy-kl-ml: Enhancing the entropy-kl-based anomaly detection on software-defined networks
The Software-Defined Networking (SDN) concept allows network innovations by leveraging
a centralized controller that commands the whole network. The controller manages the …
a centralized controller that commands the whole network. The controller manages the …
Anomaly Detection in Industrial Machinery Using IoT Devices and Machine Learning: A Systematic Mapping
SF Chevtchenko, EDS Rocha, MCM Dos Santos… - IEEE …, 2023 - ieeexplore.ieee.org
Anomaly detection is critical in the smart industry for preventing equipment failure, reducing
downtime, and improving safety. Internet of Things (IoT) has enabled the collection of large …
downtime, and improving safety. Internet of Things (IoT) has enabled the collection of large …
Detecting anomalies and attacks in network traffic monitoring with classification methods and XAI-based explainability
Assuring the network traffic safety is a very important issue in a variety of today's industries.
Therefore, the development of anomalies and attacks detection methods has been the goal …
Therefore, the development of anomalies and attacks detection methods has been the goal …
Multiclass multiple-instance learning for predicting precursors to aviation safety events
In recent years, there has been a rapid growth in applying machine learning techniques that
leverage aviation data collected from commercial airline operations to improve safety …
leverage aviation data collected from commercial airline operations to improve safety …
[HTML][HTML] Deep reinforcement learning ensemble for detecting anomaly in telemetry water level data
T Khampuengson, W Wang - Water, 2022 - mdpi.com
Water levels in rivers are measured by various devices installed mostly in remote locations
along the rivers, and the collected data are then transmitted via telemetry systems to a data …
along the rivers, and the collected data are then transmitted via telemetry systems to a data …
A graphical approach for outlier detection in gene–protein mapping of cognitive ailments: an insight into neurodegenerative disorders
SG Jacob, MMBA Sulaiman, B Bennet… - … Modeling Analysis in …, 2022 - Springer
Detecting outliers in gene–protein mapping that reveal the presence of neuro-degenerative
disorders or distinguishes between two different neuro-degenerations is an unexplored …
disorders or distinguishes between two different neuro-degenerations is an unexplored …
面向复杂数据流的集成分类综述
张喜龙， 韩萌， 陈志强， 武红鑫… - 《 广西师范大学学报》(自然 …, 2022 - gxsf.magtech.com.cn
随着大数据的快速发展, 挖掘有价值的知识可能会面临高维, 大量, 动态数据的影响,
这些复杂数据流的出现会导致分类效果下降. 为了进一步分析数据流集成分类的研究现状和面临 …
这些复杂数据流的出现会导致分类效果下降. 为了进一步分析数据流集成分类的研究现状和面临 …
Implementing machine learning in small and medium-sized manufacturing enterprises
N Iftikhar, FE Nordbjerg - … and Manufacturing Systems: Proceedings of the …, 2022 - Springer
Large enterprises in the world are making substantial investments to adopt smart
manufacturing technologies (Industry 4.0). Machine learning is one of the main driving …
manufacturing technologies (Industry 4.0). Machine learning is one of the main driving …
Advanced ML/DL-Based Intrusion Detection Systems for Software-Defined Networks
Abstract Software Defined Networking (SDN) is an innovative option with great potential for
the future growth of the Internet. It enhances the flexibility and transparency of centralized …
the future growth of the Internet. It enhances the flexibility and transparency of centralized …