Abstract
AbstractSafety investigations about electrical wiring harness caused by failures in electrical systems establish that origin of these accidents are related to electrical installation. Predictive techniques which mitigate and reduce risk of the occurrence of errors to enhance safety shall be considered. The development of machine learning has evolved towards the creation of innovative predictive algorithms which show high performance in data analysis and making predictions in the context of artificial intelligence. The Monte Carlo approach is used to validate the model performance. In this paper, Monte Carlo simulation was used to evaluate the level of the uncertainty of the selected parameters over 1000 runs. This study analyzes the reliability of the predictive algorithm in order to be implemented as an automatic error predictor in aerospace. The results obtained are within the expected range suggesting that the model used is accurate and reliable.
Publisher
Springer Nature Switzerland
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