摘要
本研究采用大数据分析方法对电解铝生产能力进行预测。首先收集与整理相关数据,然后通过机器学习、时间序列分析等方法构建预测模型。验证结果显示,所构建的模型具有较高的准确性和可靠性。分析表明,原材料价格、政策变化和市场需求等因素对电解铝生产能力具有显著影响。本研究可为电解铝行业提供有益的生产决策参考,为未来研究方向和实际应用奠定基础。
This study uses big data analysis methods to predict the production capacity of electrolytic aluminum,firstly,collects and organizes relevant data,and then constructs a prediction model through methods such as machine learning and time series analysis.The verification results show that the constructed model has high accuracy and reliability.Analysis shows that factors such as raw material prices,policy changes,and market demand have a significant impact on the production capacity of electrolytic aluminum.This study can provide useful production decision-making references for the electrolytic aluminum industry,laying the foundation for future research directions and practical applications.
作者
肖文富
余春艳
XIAO Wenfu;YU Chunyan(Tianshan Aluminum Industry Group Co.,Ltd.,Shanghai 200135,China)
出处
《科技创新与生产力》
2024年第1期22-25,共4页
Sci-tech Innovation and Productivity
关键词
电解铝
生产能力
大数据分析
预测模型
关键因素
行业决策
electrolytic aluminum
production capacity
big data analysis
prediction model
key factor
industry decision-making
