基于卡尔曼滤波算法的焦炭价格预测

摘要

焦炭价格预测研究具有重要的理论和实践意义，本文利用卡尔曼滤波算法对焦炭价格进行预测研究。建立状态空间模型时，选取焦炭价格作为唯一的状态变量，通过每一时刻变量观测值与预测值形成的新息，不断更新和迭代，以寻求最优估测值。实证分析表明，该算法对焦炭价格的跟踪和预测效果较好。%Research on coke price forecasting is of theoretical and practical signiifcance. Here, the Kalman ifltering algorithm was used to analyze the price of coke. As the only state variable, the historical coke price is sorted out to build the state space model. The algorithm makes use of innovation composed of the difference between observed and predicted values, and alows us to obtain the optimal estimated value of the coke price via continuous updating and iteration of innovation. Our results show that this algorithm is effective in the ifeld of coke price tracking and forecasting.