Работы, цитирующие эту работу

Работ: 3

Работа: A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method

1. Hybrid LSTM–DNN Architecture with Low-Discrepancy Hypercube Sampling for Adaptive Forecasting and Data Reliability Control in Metallurgical Information-Control Systems

   Jasur Sevinov, Barnokhon Temerbekova, Gulnora Bekimbetova +2

   СтатьяForecasting Techniques and ApplicationsProcesses2026Цитирований: 1

   ABIABI:AkademIndex/openalex/2026.article.000168

2. Fault Detection in Induction Motors: Recent Advances and Future Prospects

   Sarvarbek Ruzimov, Zhang Jiangzhong, Sherkhon Latipov +1

   СтатьяMachine Fault Diagnosis Techniques2024Цитирований: 0

   ABIABI:AkademIndex/openalex/2024.article.001147

3. Coexisting Modes of Oscillations and Grid-Scroll Chaos in Two Coupled Hopfield-Type Inertial Neurons: Theoretical Study and Microcontroller-Based Experiment

   Jacques Kengne, Jean Chamberlain Chedjou, Khabibullo Nosirov

   СтатьяChaos control and synchronizationInternational Journal of Bifurcation and Chaos2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.005722