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Research on Coal Price Forecast based on ARIMA and SVM combination Model

机译:基于Arima和SVM组合模型的煤炭价格预测研究

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摘要

China is the largest producer and consumer of coal in the world. Qinhuangdao Port is not only the largest coal export port in the world, but also an important coal transportation hub in China. The study of the change of coal price in Qinhuangdao Port is of great significance to the study of the change of coal price in the whole country. In this paper, in order to avoid the large prediction error of a single prediction model, an ARIMA-SVM parallel combination model is constructed, and the appropriate weight ratio of ARIMA and SVM model is obtained by calculation, so as to obtain more reliable prediction results. The results show that the international competitiveness of the domestic coal market is insufficient, the coal trading system is incomplete and depends too much on coal resources. For this reason, the government should promote the adjustment of energy structure, improve the mode of transportation, actively improve the coal futures trading system, and realize the upgrading of coal industry.
机译:中国是世界上最大的煤炭生产国和消费者。秦皇岛港不仅是世界上最大的煤炭出口港口,而且是中国重要的煤炭交通枢纽。秦皇岛港煤炭价格变化研究对全国煤炭价格变化的研究具有重要意义。在本文中,为了避免单个预测模型的大预测误差,构造了ARIMA-SVM并联组合模型,通过计算获得了ARIMA和SVM模型的适当重量比,从而获得更可靠的预测结果。结果表明,国内煤炭市场的国际竞争力不足,煤炭交易系统不完整,占煤炭资源过多。出于这个原因,政府应促进能源结构调整,提高运输方式,积极改善煤期交易系统,并实现煤炭行业的升级。

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