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《The Chinese Journal of Nonferrous Metals》 2011-04
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Prediction of functional link neural network of roof caving based on fuzzy adaptive variable weight method

ZUO Hong-yan,LUO Zhou-quan,WANG Yi-wei,WANG Shuang-ying (School of Resource and Safety Engineering,Central South University,Changsha 410083,China)  
In order to enhance the predict precision about happening rate of acoustic emission in mine,the happening rate of acoustic emission in mine was forecasted based on functional link neural network due to fuzzy adaptive variable weight algorithm by using of making some forecasting values from different single forecasting model of happening rate of acoustic emission in mine as original input values of functional link neural network,making the original input values as patulous input values of functional link neural network after the original input values being extended according to the orthogonal trigonometric function,analyzing the necessary and sufficient conditions of functional link neural network fitting and calculating the weight of functional link neural network based on fuzzy adaptive variable weight algorithm.And the roof caving can be predicted when the forecasting results is fitted by functional link neural network algorithm and the discriminant of roof caving abrupt change model.The forecasting results of happening rate of acoustic emission in some lead and zinc mine reveal that the functional link neural network forecasting method based on fuzzy adaptive variable weight algorithm is higher than that of other forecasting model and its forecasting error is smaller than 0.3%.And the precision predicting roof caving is able to be realized due to the functional link neural network forecasting.
【Fund】: 国家“十一五”科技支撑计划项目(2007BAK22B04-12 2006BAB02B05-01-02-01)
【CateGory Index】: TD327.2;TP183
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