… frontier technology of machine learning and artificial intelligence, … intrusion detection problem.
This paper studies the traditional intrusion detection technology based on learning method …

… attack detection method has low accuracy in the detection, a … , a network intrusion detection
model (DBN-SVDD) based on … Comparison with the results of other deep learning methods …

… For low-dimensional data projection thus obtained with a penalty function reuse nonlinear
support vector model and implement intrusion detection data. Finally, we use the KDD99 data …

… ways to investigate the law of ship motions and the detection of abnormal behaviours. In this
paper, various algorithms used for detecting abnormal behaviours of ship are reviewed and …

… her needs, specifying how the machines are connected, what … The best cyber ranges aim to
simulate real computer networks… using an AI technique, reinforcement learning, to determine …

… The example is, like many of the examples in books on data mining and machine learning,
is a classification problem. It comes from a study of geographical variation in plant …

… an “Artificial Intelligence 2.0 Plan,” which focused on big data, intelligent sensing, … computing,
machine learning, and swarm intelligence.The Ministry of Science and Technology has …