Integrating Deep Learning and Machine Learning for Robust Fault Diagnosis in Chemical Production Processes
A novel fault diagnosis model named three-layer deep learning network random trees (TDLN-trees) that integrates the strengths of deep learning and machine learning techniques to effectively detect and classify faults in complex chemical production processes.