This article aims to present a comprehensive review of the recent efforts and advances in
applying machine learning (ML) techniques in the area of diagnostics and prognostics of …

A crack fault is one of the damage modes most frequently occurring in gears. Identifying
different crack levels, especially for early cracks is a challenge in gear fault diagnosis. This …

Identifying gear damage categories, especially for early faults and combined faults, is a
challenging task in gear fault diagnosis. This paper proposes a new multidimensional hybrid …

Condition monitoring of rotating machinery is important to promptly detect early faults,
identify potential problems, and prevent complete failure. Four direct classification methods …

The popularity of social media networks, such as Twitter, leads to an increasing number of
spamming activities. Researchers employed various machine learning methods to detect …

Conventional k-nearest neighbor (KNN) classification approaches have several limitations
when dealing with some problems caused by the special datasets, such as the sparse …

A major issue in k-nearest neighbor classification is how to choose the optimum value of the
neighborhood parameter k. Popular cross-validation techniques often fail to guide us well in …

Abstract Floating Offshore Wind Turbines (FOWTs) operate in the harsh marine environment
with limited accessibility and maintainability. Not only failures are more likely to occur than in …

When classes are nonseparable or overlapping, training samples in a local neighborhood
may come from different classes. In this situation, the samples with different class labels may …

With the trend that the Internet is becoming more accessible and our devices being more
mobile, people are spending an increasing amount of time on social networks. However …