Recently, the operation of distribution systems does not depend on the state or utility based
on centralized procedures, but rather the decentralization of the decisions of the distribution …

The Internet of things (IoT) extends the Internet space by allowing smart things to sense
and/or interact with the physical environment and communicate with other physical objects …

Feature selection is one of the most efficient procedures for reducing the dimensionality of
high-dimensional data by choosing a practical subset of features. Since labeled samples are …

The Industrial Revolution 4.0 (IR 4.0) has drastically impacted how the world operates. The
Internet of Things (IoT), encompassed significantly by the Wireless Sensor Networks …

Because of the overgrowth of data, especially in text format, the value and importance of
multi‐label text classification have increased. Aside from this, preprocessing and particularly …

Researchers have considered multi-label learning because of its presence in various real-
world applications, in which each entity is associated with more than one class label. Since …

In cluster-based sensor networks, at each cluster, sensor nodes send the collected data to a
cluster head which aggregates and forwards them to a sink node. Data transmission from a …

By definition, the aggregating methodology ensures that transmitted data remain visible in
clear text in the aggregated units or nodes. Data transmission without encryption is …

Purpose This study aims to compare and evaluate the application of commonly used
machine learning (ML) algorithms used to develop models for assessing energy efficiency of …

Ensemble feature selection methods are used to improve the robustness of feature selection
algorithms. These approaches are a combination of several feature selection methods to …