Building a Model with AutoML in Machine Faults Detection
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-64776-5_24
Reference30 articles.
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2. Mohammed, N.A., Abdulateef, O.F., Hamad, A.H.: An IoT and machine learning-based predictive maintenance system for electrical motors. J. Européen des Systèmes Automatisés 56(4), 651–656 (2023)
3. Surantha, N., Gozali, I.D.: Evaluation of the improved extreme learning machine for machine failure multiclass classification. Electronics 12(16), 3501 (2023)
4. De Simone, L., et al.: LSTM-based failure prediction for railway rolling stock equipment. Expert Syst. Appl. 222, 119767 (2023)
5. Tarik, M., Mniai, A., Jebari, K.: Hybrid feature selection and support vector machine framework for predicting maintenance failures. Appl. Comput. Sci. 19(2), 112–124 (2023)
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