The modeling and application of cost prediction based on neural network

Cost prediction is very important for cost control, but the factors of influencing cost are much and complex. The factors affect each other, and the coupling phenomenon exists, so enterprise cost is difficult to be predicted correctly. On the basis of production cost composition model, the production cost prediction model based on neural network is established. A hybrid algorithm that trains neural network weight by real-coded adaptive mutation genetic algorithm is designed, and it overcomes the disadvantage that traditional neural network is easy to fall into local minima. Furthermore, the model is successfully applied to cost prediction in some iron & steel enterprise, and it improves the prediction accuracy.