This website uses cookies.
We use cookies to improve your online experience. By continuing to use our website we assume you agree to the placement of these cookies.
To learn more, you can find in our Privacy Policy.
Original paper

A Pythagorean-Type Fuzzy Deep Denoising Autoencoder for Industrial Accident Early Warning

Volume: 25, Issue: 6, Pages: 1561 - 1575
Published: Aug 10, 2017
Abstract
Early warning is crucial for preventing industrial accidents and mitigating damage, but current methods are often time-consuming, error-prone, and incompetent to deal with uncertainty. This paper presents a fuzzy deep neural network for early warning of industrial accidents, which equips the classical deep denoising autoencoder (DDAE) model with Pythagorean-type fuzzy parameters in order to enhance the model's representation ability and...
Paper Details
Title
A Pythagorean-Type Fuzzy Deep Denoising Autoencoder for Industrial Accident Early Warning
Published Date
Aug 10, 2017
Volume
25
Issue
6
Pages
1561 - 1575
© 2025 Pluto Labs All rights reserved.
Step 1. Scroll down for details & analytics related to the paper.
Discover a range of citation analytics, paper references, a list of cited papers, and more.