[1] 王仲颖,张有生.生态文明建设与能源转型[M].北京:中国经济出版社, 2016 [2] BP.世界能源展望2019[EB/OL]. http://www.bp.com/content/dam/bp/country-sites/zh_cn/china/home/reports/bp-energyoutlook/2019/2019eobook.pdf,2019-04-09 [3] Soldo B. Forecasting Natural Gas Consumption[J]. Applied Energy, 2012,92(4):26-37 [4] Sen D., Günay M. E., Tunç K. M. M. Forecasting Annual Natural Gas Consumption Using Socio-Economic Indicators for Making Future Policies[J]. Energy, 2019,173(15):1106-1118 [5] Wang J., Feng L., Zhao L., et al. China's Natural Gas:Resources, Production and Its Impacts[J]. Energy Policy, 2013,55(4):690-698 [6] Becerra-Fernandez M., Cosenz F., Dyner I. Modeling the Natural Gas Supply Chain for Sustainable Growth Policy[J]. Energy, 2020,205:118018 [7] 柴建,卢全莹,邢丽敏,等.中国天然气产业的发展过快了吗?[J].管理评论, 2017,29(8):23-32 [8] Ervural B. C., Beyca O. F., Zaim S. Model Estimation of ARMA Using Genetic Algorithms:A Case Study of Forecasting Natural Gas Consumption[J]. Procedia-Social and Behavioral Sciences, 2016,235(11):537-545 [9] Melikoglu M. Vision 2023:Forecasting Turkey's Natural Gas Demand between 2013 and 2030[J]. Renewable and Sustainable Energy Reviews, 2013,22:393-400 [10] Ding S. A Novel Self-adapting Intelligent Grey Model for Forecasting China's Natural-Gas Demand[J]. Energy, 2018,62(1):393-407 [11] Svoboda R., Kotik V., Platos J. Short-Term Natural Gas Consumption Forecasting from Long-Term Data Collection[J]. Energy, 2021,218:119430 [12] Qiao W., Yang Z., Kang Z., et al. Short-term Natural Gas Consumption Prediction Based on Volterra Adaptive Filter and Improved Whale Optimization Algorithm[J]. Engineering Applications of Artificial Intelligence, 2020,87:103323 [13] Shaikh F., Ji Q. Forecasting Natural Gas Demand in China:Logistic Modelling Analysis[J]. International Journal of Electrical Power&Energy Systems, 2016,77(5):25-32 [14] Hubbert M. National Academy of Sciences Report on Energy Resources:REPLY[J]. Aapg Bulletin, 1965,49(10):1720-1727 [15] 陈元千,胡建国,张栋杰. Logistic模型的推导及自回归方法[J].新疆石油地质, 1996,17(2):150-155 [16] Lin B., Wang T. Forecasting Natural Gas Supply in China:Production Peak and Import Trends[J]. Energy Policy, 2012,49(5):225-233 [17] 王婷,孙传旺,李雪慧.中国天然气供给预测及价格改革[J].金融研究, 2012,(3):43-56 [18] 舒扬,杨秋怡.基于大样本数据模型的汽车贷款违约预测研究[J].管理评论, 2017,29(9):59-71 [19] 杨波,郭剑川,谭章禄.基于国民生产总值增长率微调制的国家能源年度消费总量Logistic修正模型研究[J].中国管理科学, 2017,25(6):32-38 [20] 王超发,孙静春.基于错分代价的用户换手机的分类器阈值和预期风险研究[J].管理评论, 2018,30(12):122-130 [21] Hansen J. P., Narbel P. A., Aksnes D. L. Limits to Growth in the Renewable Energy Sector[J]. Renewable and Sustainable Energy Reviews, 2017,70(4):769-774 [22] Nusinovici S., Tham Y. C., Chak Yan M. Y., et al. Logistic Regression Was as Good as Machine Learning for Predicting Major Chronic Diseases[J]. Journal of Clinical Epidemiology, 2020,122(6):56-69 [23] Yu X., Ye S. The Universal Applicability of Logistic Curve in Simulating Ecosystem Carbon Dynamic[J]. China Geology, 2020, 3(2):292-298 [24] 周明儒,林武忠,倪明康.奇异摄动导论[M].北京:科学出版社出版, 2014 [25] Lu J., Zhao S., Sun Y., et al. Gas Production Peaks in China:Research and Strategic Proposals[J]. Natural Gas Industry B, 2018,5(4):371-379 [26] Li N., Wang J., Wu L., et al. Predicting Monthly Natural Gas Production in China Using a Novel Grey Seasonal Model with Particle Swarm Optimization[J]. Energy, 2021,215:119118 |