神经网络预测模型在轮胎骨架材料市场预测的应用

Application of neural network prediction model to tire frame materials market prediction

神经网络模型具有很强的非线性映射能力,特别适合于各种数据的处理和预测;胎圈钢丝、钢帘线的产销量与汽车产量、轮胎用量、国内GDP、盘条产量等因素具有较强的正相关性,通过建立DEEP神经网络模型,组织样本数据,利用神经网络的黑箱特性进行了预测尝试,得出未来5年中国轮胎骨架材料的需求处于缓慢增长的平台发展期。

Neural network model has strong nonlinear mapping ability,and is particularly suitable for processing and forecasting various data.Bead wire and steel cord have strong positive correlation with automobile output,tire consumption,GDP,wire rod output and other factors.By establishing DEEP neural network model,organizing sample data,and using black box characteristics of neural network to make prediction attempts,it is concluded that China’s tire framework materials are in platform development period of slow growth in the next five years.