Application of the rough sets in identification of material property parameter via neural network
SU Chun-jian · Duanya jishu · 2007
The real-time identification via neural network is an important subject in intellectual deep drawing of sheet metal.Because of the redundancy of training data,it makes the convergence of BP neural network slow and imprecise.Using the data reduction and classify function of rough sets,the training data of surplus attribute can be(deleted) and the structure of the neural network can be optimized.Experiments prove that the optimized network converges more quickly and accurately.The relative prediction error precisions are all below 6%.