ArticleBioMed research international2022
Hospital Intelligent Power Operation and Maintenance Information Evaluation with the Long and Short Memory Neural Network.
Article in BioMed research international, 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 It has been retracted, and should not be counted.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: Hospital Intelligent Power Operation and Maintenance Information Evaluation with the Long and Short Memory Neural Network.BioMed research international · 2024Article
Corrections and comments
- Retraction · 2024-01-09Concerns/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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The invention describes a deep learning-based technique for monitoring power grid information operation and maintenance. Based on the time series data information in the power grid information operation and maintenance monitoring system, this method obtains the cleaned time series data through appropriate data preprocessing technology. This also uses the long-term and short-term memory neural network to realize the prediction function of the time series data to be detected. The reason behind is to construct the normal behavior model of the time series. Additionally, the control chart based on an exponentially weighted moving average is employed to determine whether the time series to be discovered contains any anomalous and abnormal phenomena. In the area of power grid information operation and maintenance monitoring, the method of invention is designed to counter anomaly. This phenomenon is universal in nature and has significant scientific importance for guiding treatment after the anomaly is discovered. Additionally, it guards against serious faults that the abnormality might bring about.
Indexed as
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.