Translator Disclaimer
1 January 2015 Forecasting the Coke Price Based on the Kalman Filtering Algorithm
Zhu Meifeng, Zhao Guohao
Author Affiliations +
Abstract

Research on coke price forecasting is of theoretical and practical significance. Here, the Kalman filtering 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 allows 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 field of coke price tracking and forecasting.

Zhu Meifeng and Zhao Guohao "Forecasting the Coke Price Based on the Kalman Filtering Algorithm," Journal of Resources and Ecology 6(1), 60-64, (1 January 2015). https://doi.org/10.5814/j.issn.1674-764x.2015.01.008
Received: 10 September 2013; Accepted: 1 August 2014; Published: 1 January 2015
JOURNAL ARTICLE
5 PAGES


Share
SHARE
KEYWORDS
coke price
forecasting
Kalman filtering algorithm
state space model
RIGHTS & PERMISSIONS
Get copyright permission
Back to Top