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Article summary:
1. The flexural rigidity of hangers should be identified in addition to the basic frequency when determining hanger tension.
2. The additional mass method (AMM) is proposed, using mass as an additional condition for tension identification.
3. Artificial Neural Network (ANN) is used to estimate the flexural rigidity and tension of hangers based on measured frequencies before and after the attachment of mass.
Article analysis:
The article provides a detailed overview of the use of Artificial Neural Network (ANN) to identify flexural rigidity and tension of short hangers with adding mass. The authors present their research in a clear and concise manner, providing evidence for their claims through examples and case studies. However, there are some potential biases that should be noted. For example, the authors do not explore any counterarguments or alternative methods for identifying flexural rigidity and tension of short hangers with adding mass, which could lead to a one-sided view of the topic. Additionally, there is no discussion about possible risks associated with using ANN for this purpose, such as potential errors or inaccuracies in the results due to incorrect data input or other factors. Furthermore, while the authors provide evidence for their claims through examples and case studies, they do not provide any evidence from external sources that could further support their findings. In conclusion, while this article provides an interesting overview of ANN usage for identifying flexural rigidity and tension of short hangers with adding mass, it does not provide enough evidence or exploration into alternative methods or potential risks associated with this approach.