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PSO, FA and GD algorithms for predicting industry failures

Hamameh Imad Nekhadovich  (Postgraduate Student, Federal State Budgetary Educational Institution of Higher Education "MIREA — Russian Technological University", Moscow)

One of the goals of the smart industry is to reduce the number of failures, which reduces costs. To achieve this goal, technological processes are monitored and divided into multiple processes and the probability of success per process are calculated. The main contribution to this work was the proposal of methods for training neural networks.

Keywords:Artificial neural network; Fault prediction; Machine learning; Algorithms inspired by nature.
 

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Citation link:
Hamameh I. N. PSO, FA and GD algorithms for predicting industry failures // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2022. -№04. -С. 130-136 DOI 10.37882/2223-2966.2022.04.33
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