The optical insensitivity of non-optically active water quality parameters (NAWQPs) presents
a significant challenge for remote sensing-based quantitative monitoring, which is an …

As the critical component of satellite flywheels, bearings should be tested and selected on
the ground before the flight. Aiming at the condition assessment requirements of flywheel …

With the rapid development of the Big Data and Internet of Things (IoT), Big Data
technologies have emerged as a key data analytics tool in IoT, in which, data clustering …

Spectral clustering is one of the most popular clustering methods. However, how to balance
the efficiency and effectiveness of the large-scale spectral clustering with limited computing …

In recent years, metaheuristic algorithms have been widely used in solving clustering
problems because of their good performance and application effects. Krill herd algorithm …

Spectral clustering algorithm suffers from high computational complexity due to the eigen
decomposition of Laplacian matrix and large similarity matrix for large-scale datasets. Some …

Spectral clustering has been shown to be more effective than most of the traditional
clustering algorithms. However, the heavy computational cost of spectral clustering limits its …

Due to the massive data increase in different Internet of Things (IoT) domains such as
healthcare IoT and Smart City IoT, Big Data technologies have been emerged as critical …

The Performance of rolling element bearings has a significant influence on reliability and
safety in the various engineering fields. While heading toward the condition evaluation of …

Web Information Retrieval (IR) has been successful with page-ranking algorithms that order
web pages based on their rankings and relevance. These ranking algorithms are one of the …