Investigation and Development of Recursive Neural Networks for the Analysis of Industrial Processes
Tóm tắt
We consider the application of neural-network approaches to time-series analysis for the investigation of modern production processes. As an application of the proposed techniques, we study the optimization problem for a fixed set of process outputs. We examine and experimentally evaluate the most appropriate algorithms for industrial process modeling. Methods are proposed for choosing the algorithm architecture and parameters. An optimization method is advanced that allows for the technological constraints in the objective functions.
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