Artificial Intelligence White Papers
Neural Networks to Predict and Control Pyro-Metallurgical Processes
Overview The multi-variable, non-linear models produced by using neural networks have demonstrated that the neural network approach to metallurgical processes is definitely a breakthrough for the metallurgical plant control and optimisation. The work done recently has been reported on the domains of pyro-metallurgical processes and other very relevant processes such as control of submerged arc furnace for ferro-alloy production, predictive control of a refractory gold plant, optimisation of gas-loop process, and prediction and control of blast furnace. Neural networks represent, in some sense, a revolution in the approach to do high-dimensional non-linear model in order to be able to predict and control the pyro-metallurgical processes.
| Publisher | Business Execution - Solution & Technologies (BEST) | File Format | HTML |
|---|---|---|---|
| Date Published | August 2003 | Downloads | 147 |
| Format | White Papers | ||
| Topics | |||
-
Did you find this white paper useful? 3 out of 6 users found this white paper useful
White Paper RSS
Download
Register
