This research presents a new generic deep learning (DL) framework for anomaly detection
in the Internet of Everything (IoE). It combines decomposition methods, deep neural …

Recently, some progress has been made in anomaly detection for data streams. However,
these methods still exhibit deficiencies in effectively balancing computational efficiency and …

In this paper, a memory-efficient outlier detection (MEOD) approach for streaming data is
proposed. The approach uses a local correlation integral (LOCI) algorithm for outlier …

Outlier detection techniques detect abnormal behavior in data and are useful in a variety of
applications. In a real-life scenario, various applications generate large-scale data every …

In this paper, a memory-efficient outlier detection (MEOD) approach for streaming data is
proposed. The approach uses a local correlation integral (LOCI) algorithm for outlier …

The complex nonlinear and strongly coupled dynamics of small unmanned helicopters make
mathematical modeling challenging. Traditional approaches often rely on least squares …