The paper used Matlab to program for single-layer BP neural network, selected the annual energy consumption data as the training sample and inspection sample to train BP neural network, then, predict the future China's energy consumption quantity.
Using virtual reality computer simulation technology, by researching of the ethylene production process equipment and production process, Ethylene cracking plant modeling and simulation training system development were completed. Ethylene cracking device 3D modeling development scheme and process were introduced, which include the use of 3DMAX software for 3D modeling design, combined with the virtual reality software realization of human-computer interactive function design. Based on Virtual reality technology, 3D simulation system of ethylene plant was realized.
On the basis of the analysis of ethylene cracking process, equipment, process control and operation conditions, using process control system simulation platform, Ethylene cracking plant DCS modeling and simulation training system were developed. Using continuous modeling method, combined mechanism modeling with test data analysis, DCS control system mathematic model was established, by which normal operation, start,shutdown process and accident treatment process were simulated. The online evaluating system was developed too, which supply a virtual platform for the training of ethylene cracking process.
Aiming at the control of the secondary regulation speed control system, A new-type of fuzzy neural networks is used in the parameters setting of PID controller, which is helpful to overcome the uncertainty, nonlinearity and time-variability of the system. By establishing the mathematic model of the system, Simulation research are carried out. Simulation results indicate that the fuzzy neural networks model improves the dynamic response of the system.
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