Resampling imbalanced data for network intrusion detection datasets
S Bagui, K Li - Journal of Big Data, 2021 - Springer
Abstract Machine learning plays an increasingly significant role in the building of Network
Intrusion Detection Systems. However, machine learning models trained with imbalanced …
Intrusion Detection Systems. However, machine learning models trained with imbalanced …
A hybrid artificial intelligence algorithm for fault diagnosis of hot rolled strip crown imbalance
R Zhang, Y Qi, S Kong, X Wang, M Li - Engineering Applications of Artificial …, 2024 - Elsevier
In the production process of hot continuous rolling, due to the imbalance between the
number of normal cases and fault cases, the traditional supervised learning methods are …
number of normal cases and fault cases, the traditional supervised learning methods are …
Wind power short-term forecasting model based on the hierarchical output power and poisson re-sampling random forest algorithm
J Hao, C Zhu, X Guo - IEEE Access, 2020 - ieeexplore.ieee.org
Under the background of big data, the use of massive online data to improve the real-time
characteristics and reliability of wind power prediction and to reduce the impact of wind …
characteristics and reliability of wind power prediction and to reduce the impact of wind …
Construction of smart home-school collaboration system based on distributed cluster technology
Y Yang - 2021 International Conference on Artificial Intelligence …, 2021 - ieeexplore.ieee.org
With the development of science and technology and the rapid popularization of the network
technology, digital devices are widely used, and electronic devices such as mobile phones …
technology, digital devices are widely used, and electronic devices such as mobile phones …