Anomaly detection has numerous applications in diverse fields. For example, it has been
widely used for discovering network intrusions and malicious events. It has also been used …

This paper introduces a new model to identify collective abnormal human behaviors from
large pedestrian data in smart cities. To accurately solve the problem, several algorithms …

The printed circuit boards (PCBs) industry is one of the fastest-growing industries in recent
decades. The PCB manufacturing process is highly complicated and severely affected by …

Graph-based intelligent systems are emerging in the field of transportation systems.
Knowledge graphs help to provide semantic and interconnectivity capabilities to the …

Belief rule-base (BRB) expert system is one of recognized and fast-growing approaches in
the areas of complex problems modeling. However, the conventional BRB has to suffer from …

Many research areas depend on group anomaly detection. The use of group anomaly
detection can maintain and provide security and privacy to the data involved. This research …

This article introduces two new problems related to trajectory outlier detection:(1) group
trajectory outlier (GTO) detection and (2) deviation point detection for both individual and …

Outlier detection plays an important role in data mining because it can improve the
performance of data analysis. Most outlier detection algorithms focus on numerical or …

Outlier detection is widely used in many fields, such as intrusion detection, credit card fraud
detection, medical diagnosis, and so on. Existing outlier detection algorithms are mostly …

Outlier detection in high dimensional data faces the challenge of curse of dimensionality,
where irrelevant features may prevent detection of outliers. In this research, we propose a …