Natural computing for mechanical systems research: A tutorial overview

By Keith Worden, Wieslaw J. Staszewski, James Hensman. 2011

294 citations recorded by the source corpus.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/94e798cec79eab7c4646ea0ba672431e76dad4f0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Hadi Salehi
2. Jing Lin
3. Steven X. Ding
4. Yaguo Lei
5. Rigoberto Burgueño
6. Saibo Xing
7. Feng Jia

Citations in the corpus

• Tackling Faults in the Industry 4.0 Era—A Survey of Machine-Learning Solutions and Key Aspects (2019, background): “Fault detection and diagnosis mainly involves three steps, that is, data collection, data processing for feature extraction and finally, fault classification [42].”
• A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis (2019, unknown): “in the data-driven fault diagnosis [6].”
• Emerging artificial intelligence methods in structural engineering (2018, background): “, support vector machines, neural networks, decision trees, and clustering algorithms [91,99].”
• An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data (2016, background): “It can be found that plenty of studies have been conducted on intelligent fault diagnosis and achieved good results [9].”