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《Journal of Jilin University(Information Science Edition)》 2009-01
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Neural Networks with Weight Functions and Application in Energy Consumption Forecasting of Ore Dressing Plant

ZHANG Niao-na1,2,CHEN Fang1,ZHANG De-jiang1(1.College of Electrical and Electronic Engineering,Changchun University of Technology,Changchun 130012,China;2.College of Automotive Engineering,Jilin University,Changchun 130022,China)  
The characteristics of multivariate strong coupling,time varying,nonlinear and long time-delay in the magnetic separation process of Dagushan Ore Dressing Plant,make it difficult to use the conventional methodologies of optimal control based on mathematical model.With simple network topology constituted by input layer and output layer only,the new neural network with weight functions is proposed.The weight is function instead of traditional constant.On constructing of weight function,according to the production data in actual production process of Ore Dressing Plant and the gap of these data,different interpolation functions are selected as the weight functions.Simulation examples show the good performance of this method that little calculation work,high calculation speed,with no local minimum and slow convergence problems.Model mentioned above has minor error and the better prediction effect is obtained.
【Fund】: 国家科技支撑基金资助项目(2007BAE17B04)
【CateGory Index】: TD928;TP183
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