The internet has become an indispensable tool for organizations, permeating every facet of
their operations. Virtually all companies leverage Internet services for diverse purposes …

Landslides are a common natural disaster that can cause casualties, property safety threats
and economic losses. Therefore, it is important to understand or predict the probability of …

The need to avoid computer system breaches is increasing. Many researchers have
adopted different approaches, such as intrusion detection systems (IDSs), to handle various …

As an important task in data mining, feature selection can improve the performance of
classification by eliminating the redundant or irrelevant features in original data. It is mainly …

Regarding to the huge number of connections and the large flow of data on the Internet,
Intrusion Detection System (IDS) has a difficulty to detect attacks. Moreover, irrelevant and …

Both software defined networks and the Internet of Things are new topics that are being
heavily employed in the information technology industry and academia. Due to their fame …

In this paper, an adaptive network intrusion detection method using fuzzy rough set-based
feature selection and GA-GOGMM-based pattern learning is presented. Based on the fuzzy …

Anomaly detection is an important method for monitoring network traffic where is important to
successfully distinguish normal traffic from abnormal traffic. For this purpose, one could use …

An effective bearing fault diagnosis model based on machine learning is proposed in this
study. The model can separate into three stages: feature extraction, feature selection, and …

Intrusion detection systems (IDSs) play a crucial role in ensuring the security and integrity of
Internet of Things (IoT) networks by blocking unwanted packets and facilitating secure traffic …