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About A Pythagorean-Type Fuzzy Deep Denoising Autoencoder For Industrial Accident Early Warning
This document summarizes a research article that proposes a Pythagorean-type fuzzy deep denoising autoencoder (PFDDAE) model for early warning of industrial accidents. Traditional early warning approaches rely heavily on expert knowledge and experience, but the proposed PFDDAE model uses deep learning to better handle uncertainty in risk factors. The model equips a classical deep denoising autoencoder with Pythagorean-type fuzzy parameters to enhance representation ability and robustness. Experiments on Chinese industrial accident datasets show the PFDDAE achieves higher accuracy than other models and may have helped prevent a 2014 explosion if adopted earlier.
Detailed Information
| Author: | ['Gonzalo'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 15 |
| Language: | English |
| Format: | |
| Price: | FREE |
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