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作 者:王利宁[1,2] 单卫国 王婧[1,2] 李男 张荻萩[1,2] 刘凯雷 WANG Lining;SHAN Weiguo;ANG Jing;LI Nan;ZHANG Diqiu;LIU Kailei(CNPC Economics and Technology Research Institute;Key Laboratory of Oil and Gas Market Simulation and Price Forecast,CNPC)
机构地区:[1]中国石油集团经济技术研究院 [2]中国石油集团油气市场模拟与价格预测重点实验室
出 处:《国际石油经济》2024年第S01期55-60,共6页International Petroleum Economics
摘 要:中国石油集团经济技术研究院石油市场研究团队经过多年探索实践,构建了以供需基本面研究为核,以非基本面要素为补充的体系化石油市场分析框架,能够较为准确地研判石油市场供需趋势和价格走势,在国内外学术界和行业内赢得了广泛认可和良好声誉。面对更趋复杂的能源发展环境,进一步提升石油市场研究的科学性、准确性和前瞻性的难度指数级提升。为此,研究团队探索引进大数据与人工智能等方法,基于智能化平台将大数据、人工智能等方法与传统方法有机结合,形成了一套具有自主知识产权的创新性研究方法及模型体系,解决了石油市场研究中官方数据滞后、模型预测精度不足等问题,实现了数据由低频向高频、由少维度向多维度升级。After years of exploration and practice,the oil market research team of CNPC Economics and Technology Research Institute has constructed a systematic oil market analysis framework with supply and demand fundamentals as the core,supplemented by non-fundamental elements,and is able to accurately study the supply and demand trend and price trend in the oil market,which has gained wide recognition and a good reputation in domestic and international academic circles and industry.In the face of the increasingly complex energy development environment,the dificulty of further improving scientific,accurate and forward-looking oil market research has increased exponentially.To this end,the research team explored the introduction of big data and artificial intelligence methods,organically combined big data,artificial intelligence and other methods with traditional methods based on an intelligent platform,and formed a set of innovative research methods and model systems with independent intellectual property rights,which solved the problems of lagging official data and insufficient model prediction accuracy in oil market research,and upgraded the data from low-frequency to high-frequency,and from less dimensionality to multi-dimensionality.
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