西安石油大学学报（自然科学版）2026，Vol.41Issue(3)：35-43,9.DOI:10.3969/j.issn.1673-064X.2026.03.004
基于SSA-FIG-LSTM模型的天然气负荷区间预测
Research on Natural Gas Load Interval Prediction Based on SSA-FIG-LSTM Model
摘要
Abstract
Natural gas load data is characterized by significant fluctuation,high noise level,and redundancy.The prediction effect is poor using single model prediction method,and point forecast results fail to reflect the randomness of load fluctuation.Therefore,a natu-ral gas load interval forecasting method based on singular spectrum analysis(SSA),fuzzy information granulation(FIG),and long short-term memory(LSTM)is proposed.Using SSA,the raw data is decomposed and reconstructed into trend component,periodic com-ponent,and noise component;The noise component is processed by FIG,effective information is extracted from high-frequency data,and the maximum,minimum,and average values of window fluctuations are extracted to replace the original noise component;The feature se-lection is performed according to the characteristics of each component,and the prediction is performed by combining feature sequence with component sequence and inputting into the LSTM model;The predicted results of various components are effectively integrated u-sing the idea of"point+interval"to form final prediction interval.Compared with other traditional models,the proposed method has higher prediction accuracy and narrower prediction interval,and the prediction results can objectively reflect the uncertainty of load fluc-tuations.关键词
天然气负荷/区间预测/奇异谱分析/模糊信息粒化/长短期记忆Key words
natural gas load/interval prediction/singular spectrum analysis/fuzzy information granulation/long short-term memory分类
能源科技引用本文复制引用
张芷晨,邵必林..基于SSA-FIG-LSTM模型的天然气负荷区间预测[J].西安石油大学学报（自然科学版）,2026,41(3):35-43,9.基金项目
国家自然科学基金面上项目"面对不确定因素的天然气负荷预测及用户行为检测方法研究"(62072363) （62072363）
