基于大模型应用的天然气负荷预测

Natural Gas Load Prediction Based on Large Model Applications

文中深入探讨了基于大模型的天然气负荷预测方法。在天然气行业,准确预测负荷对优化资源分配和降低运营成本至关重要。首先,分析了预测所需的关键数据源和类型,包括历史负荷数据、气候模式和用户行为等。接着,详细讨论了特征提取的方法和技术,以及数据可视化在初步分析中的应用。文中还对传统预测方法与基于大模型的预测方法进行了对比分析,并强调了后者在处理大规模、复杂数据集方面的优势。最后,探讨了基于数据驱动的决策制定过程和风险管理策略,突出了其在天然气负荷预测中的重要性。

This paper delves into the methodology of natural gas load forecasting based on large models.In the natural gas industry,accurate load prediction is crucial for optimizing resource allocation and reducing operational costs.Firstly,the key data sources and types required for prediction are analyzed,including historical load data,climate patterns,and user behavior.Subsequently,the paper discusses in detail the methods and techniques of feature extraction,as well as the ap-plication of data visualization in preliminary analysis.A comparative analysis is also conducted between traditional forecas-ting methods and those based on large models,emphasizing the latter's advantages in handling large-scale and complex datasets.Finally,the paper explores the process of data-driven decision-making and risk management strategies,high-lighting their significance in natural gas load forecasting.