中国天然气物流需求量预测—基于自适应过滤和马尔科夫模型

Forecasting of Natural Gas Logistics Demand Volume in China:Based on Adaptive Filtering and Markov Model

针对中国天然气物流需求量预测问题,改变传统使用单一数学方法的预测方式,在使用自适应过滤法的基础上,利用预测值与实际值的关系构建马尔科夫矩阵修正结果。并与使用三次指数平滑法的预测结果进行对比,验证其准确性。最后根据此方法预测2015-2020年中国天然气物流需求量,为规划建设提供依据。

In this paper, in view of the problems in the forecasting of the natural gas logistics demand volume in China, we modified the traditional forecasting method, and on the basis of the adaptive filtering method, built a Markov matrix for the modification. Next we compared the result from the modified method with that of the tertiary exponential smoothing process to verify its accuracy. At the end, we used this method to forecast the natural gas logistics demand volume for the period between 2015 and 2020.