USING RECURRENT NEURAL NETWORKS TO CALCULATE THE RELIABILITY OF SENSORS

The article presents the main stages of using recurrent neural networks to calculate the reliability of sensors. The principles of constructing a model for calculating reliability using neural networks, the stages of developing this model are shown. An example of the use of recurrent neural networks is considered to calculate the reliability of sensors.

Publication Details

Journal: Zenodo (CERN European Organization for Nuclear Research)
Published: 2025-03-10
DOI: https://doi.org/10.5281/zenodo.15003585
Primary Topic: Electric Power Systems and Control
Type: article
Field-Weighted Citation Impact: 0.00

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article

USING RECURRENT NEURAL NETWORKS TO CALCULATE THE RELIABILITY OF SENSORS

Mar 10, 2025

Zenodo (CERN European Organization for Nuclear Research)

Electric Power Systems and Control

article

USING RECURRENT NEURAL NETWORKS TO CALCULATE THE RELIABILITY OF SENSORS

March 10, 2025article en

Abstract

Zenodo (CERN European Organization for Nuclear Research)

Industry, innovation and infrastructure

Openalex Percentile: Top 54%

Electric Power Systems and Control

DOI Open Access PDF OpenAlex

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USING RECURRENT NEURAL NETWORKS TO CALCULATE THE RELIABILITY OF SENSORS · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS