Application of Nonlinear Quantization CMAC to the Proportion Mixture Model of Digesting Recycled Liquor

The adaptive algorithm is adopted to design the concept mapping of cerebella model articulation controller(CMAC) neural network.The nonlinear quantization CMAC is presented to improve the speed and accuracy of calculation to meet the complex and dynamic demand under the nonlinear and realtime controlling environment.A proportion mixture time series prediction model of digesting recycled liquor by the nonlinear quantization CMAC is presented to forecast the quantity of recycled liquor accurately and fast.The quantity of recycled liquor is optimized on the basis of the model.The test shows that the accuracy and speed of the time series prediction model has obvious advantages.The model has been applied to certain alumina plant to optimize dynamically the recycled liquor quantity to save the raw materials.