Network intrusion is a growing threat with potentially severe impacts, which can be
damaging in multiple ways to network infrastructures and digital/intellectual assets in the …

This paper describes a focused literature survey of self-organizing maps (SOM) in support of
intrusion detection. Specifically, the SOM architecture can be divided into two categories, ie …

In an age when the Internet has become the backbone of communications, a robust and safe
network environment is critical. Intrusion detection techniques are thus valuable for IT …

In recent years, the field of unsupervised learning in neural networks has witnessed
significant advancements. This innovative learning technique holds great promise for …

As an artificial neural network method, self-organizing mapping facilities efficient complete
and visualize high-dimensional data topology representation, valid in a number of …

Most of the existing Bayesian clustering algorithms perform well on the balanced data. When
the data are highly imbalanced, these Bayesian clustering algorithms tend to strongly favor …

In this paper, we introduce a novel approach to enhance the accuracy and convergence
behavior of Self-Organizing Maps (SOM) by incorporating a reweighted zero-attracting term …

针对移动机器人环境认知问题, 受老鼠海马体位置细胞在特定位置放电的启发,
构建动态增减位置细胞认知地图模型(Dynamic growing and pruning place cells-based …

The current state of the art systems in Artificial Intelligence (AI) enabled intrusion detection
use a variety of black box methods. These black box methods are generally trained using …

A new evaluation mechanism was proposed to enhance the representation of data topology
in the directed batch growth hierarchical self-organizing mapping. In the proposed …