Accurately predicting product cost is meaningful to cost control of mineral processing production process. Complex factors which influence product cost affect each other and the coupling phenomenon exists, so it is im...
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Accurately predicting product cost is meaningful to cost control of mineral processing production process. Complex factors which influence product cost affect each other and the coupling phenomenon exists, so it is important and difficult to predict the product cost. Mineral processing product cost forecasting model built by using Adaptive Neuro-Fuzzy Inference System (ANFIS), and T-S fuzzy model identified by subtractive clustering, least squares and gradient descent algorithm. Simulation analysis made to test the forecast effect of the proposed model based on the data of integration fine iron mine cost and its influence factors, results of simulation show the feasibility and effectiveness of the proposed method.
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