Fault Detection and Isolation in Industrial Processes Based On RNN. Deep Learning Approach

      Аннотация: Deep Learning is a subset collection of Machine Learning concerned where neural network algorithms inspired by human brain learn from large amount of data through several layers for nonlinear transformation, Deep learning domain techniques allows to extract features automatically from the Industrial fault detection dataset. Since it has the strong learning ability that can improve the utilization of the dataset for the feature extraction. It determines Industrial Processes fault in the input data by simulating the way the human brain detects the fault in the industrial processes.

Ключевые слова: RNN, DAE, Genetic algorithms, Particle Swarm, Optimization