Abstract
Abstract Considering the difficulty to built mechanisms models for complex industrial processes, this paper proposes a data-driven modelling method. This method includes a process for processing real industrial data and an improved deep learning algorithm. The data processing flow completes the basic preparation work for the raw data, and the improved algorithm calculates the model based on this. The improved algorithm is Arima-ACNN-LSTM coupling algorithm, which can enhance the original LSTM algorithm by adopting CNN and Attention mechanisms. The experimental results show that, the accuracy of the model using the proposed improved algorithm is better than that using the ARIMA algorithm, the LSTM algorithm and the ARIMA-LSTM coupling algorithm. So this paper provides an inspiring approach for industrial processes modelling with complex characteristics.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
