| 基于加权移动平均法的铁矿石价格预测 |
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| 引用本文： | 王忠康,顾晓薇,胥孝川,黄晓红.基于加权移动平均法的铁矿石价格预测[J].中国矿业,2017,26(7). |
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| 作者姓名： | 王忠康 顾晓薇 胥孝川 黄晓红 |
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| 作者单位： | 东北大学 资源与土木工程学院,东北大学 资源与土木工程学院,东北大学 资源与土木工程学院,东北大学 资源与土木工程学院 |
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| 基金项目： | 国家自然科学基金资助项目(编号：51474049,51674062,51604061)；辽宁省自然科学基金资助项目(编号：15351090157)；辽宁省教育厅重点实验室基础研究项目(编号：15351090157)。 |
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| 摘 要： | 铁矿石的预期价格对矿业公司的决策异常重要,由于影响铁矿石价格的因素众多,加之近些年价格波动明显,对其进行准确预测较为困难。基于加权移动平均法,综合分析铁矿石价格的可能走势,调整权值,考虑最近三年的铁矿石历史价格,得到铁矿石市场价格的改进预测值,分别为2017年525.36元/t、2018年535.13元/t、2019年548.13元/t、2020年551.67元/t,年平均增长率约为3.73%。结合各大相关机构的预测研究,通过概率分布得出未来几年铁矿石价格年均3.73%的增长率可信度较高,可为相关企业决策提供参考。
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| 关 键 词： | 铁矿石价格 加权移动平均法 改进预测 增长率 概率分布 |
| 收稿时间： | 2017/2/17 0:00:00 |
| 修稿时间： | 2017/5/17 0:00:00 |
Forecasting of Iron Ore Price Based on Weighted Moving Average Method |
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| WANG Zhong-kang,GU Xiao-wei,XU Xiao-chuan and HUANG Xiao-hong.Forecasting of Iron Ore Price Based on Weighted Moving Average Method[J].China Mining Magazine,2017,26(7). |
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| Authors: | WANG Zhong-kang GU Xiao-wei XU Xiao-chuan and HUANG Xiao-hong |
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| Affiliation: | School of Resources and Civil Engineering,Northeastern University,School of Resources and Civil Engineering,Northeastern University,School of Resources and Civil Engineering,Northeastern University,School of Resources and Civil Engineering,Northeastern University |
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| Abstract: | The expected price of iron ore is extremely important to the mining companies to make decisions. Due to many factors influencing the price of iron ore and the obvious price fluctuation in recent years, it is more difficult to predict the price of iron ore accurately. Based on the weighted moving average method, this paper analyzes the possible trend of iron ore price, adjusts the weight value, and takes the historical price of iron ore in the last three years to get the improved forecasting price of iron ore, which is 525.36 yuan / ton in 2017 , 535.13 yuan / ton in 2018, 548.13 yuan / ton in 2019, 551.67 yuan / ton in 2020, and the average annual growth rate is about 3.73%. Combined with the prediction of the relevant institutions, the average annual growth rate of 3.73% has a higher confidence by analyzing the probability distribution of iron ore price in the next few years, so it can provide a reference for the relevant business to make decisions. |
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| Keywords: | iron ore price weighted moving average method improved forecasting growth rate probability distribution |
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