ArticleApplied bionics and biomechanics2022
An Intelligent Health Monitoring Model Based on Fuzzy Deep Neural Network.
Article in Applied bionics and biomechanics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Retracted: An Intelligent Health Monitoring Model Based on Fuzzy Deep Neural Network.Applied bionics and biomechanics · 2023Article
Corrections and comments
- Retraction · 2023-12-20Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An intelligent health detection model is a new technology developed under an artificial intelligence environment, which is of great significance to the care of the elderly and other people who cannot take care of themselves. This paper comprehensively reviews the structural health monitoring method based on an intelligent algorithm, introduces the application model of neural networks in structural health monitoring in detail, and points out the shortcomings of using neural network technology alone. On the basis of previous work, the genetic algorithm and fuzzy theory were introduced as optimization tools, and a new neural network training algorithm was constructed by combining genetic algorithm, fuzzy theory, and neural network technology for structural health monitoring research. Aimed at the shortcoming of insufficient samples for training neural networks based on experimental data, this paper proposes to use the finite element method to construct a genetic fuzzy RBF neural network after corresponding processing of the first six-order bending modal frequencies of the structure, so as to realize the localization and detection of delamination damage of composite beams.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.