Process fault detection and diagnosis (FDD) is an essential tool to ensure safe production in
chemical industries. After decades of development, despite the promising performance of …

Process monitoring plays an important role in chemical process safety management, and
fault diagnosis is a vital step of process monitoring. Among fault diagnosis researches …

Abstract Internet of Things (IoT) connects the physical world and the cyber world to offer
intelligent services by data mining for big data. Each big data sample typically involves a …

The possibilistic fuzzy c-means clustering (PFCM) algorithm is a hybridization of possibilistic
c-means clustering (PCM) and fuzzy c-means clustering (FCM) algorithms. However, there …

This paper investigates how to fuse grayscale and thermal video data for detecting
foreground objects in challenging scenarios. To this end, we propose an intuitive yet …

An axial piston pump is a key component in hydraulic systems and has been widely used in
industries. Failure of this component will result in costly downtime and serious accidents …

Sentiment classification plays a significant role in everyday life, in political activities, in
activities relating to commodity production, and commercial activities. Finding a solution for …

In this brief, a hybrid model combining the fuzzy min-max (FMM) neural network and the
classification and regression tree (CART) for online motor detection and diagnosis tasks is …

Data-driven fault diagnosis, known to be simple and convenient, is more suitable for
diagnosing the complicated spacecraft systems, eg the satellite power system. Nevertheless …

In 1993, Krishnapuram and Keller proposed possibilistic c-means (PCM) clustering, where
the PCM had various extensions in the literature. However, the PCM algorithm with its …