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A comparison of models for forecasting the residential natural gas demand of an urban area

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  1. Bartłomiej Gaweł & Andrzej Paliński, 2021. "Long-Term Natural Gas Consumption Forecasting Based on Analog Method and Fuzzy Decision Tree," Energies, MDPI, vol. 14(16), pages 1-26, August.
  2. Konstantinos Papageorgiou & Elpiniki I. Papageorgiou & Katarzyna Poczeta & Dionysis Bochtis & George Stamoulis, 2020. "Forecasting of Day-Ahead Natural Gas Consumption Demand in Greece Using Adaptive Neuro-Fuzzy Inference System," Energies, MDPI, vol. 13(9), pages 1-32, May.
  3. Tong, Jianfeng & Liu, Zhenxing & Zhang, Yong & Zheng, Xiujuan & Jin, Junyang, 2023. "Improved multi-gate mixture-of-experts framework for multi-step prediction of gas load," Energy, Elsevier, vol. 282(C).
  4. Jason Runge & Radu Zmeureanu, 2021. "A Review of Deep Learning Techniques for Forecasting Energy Use in Buildings," Energies, MDPI, vol. 14(3), pages 1-26, January.
  5. Dinis, Duarte & Barbosa-Póvoa, Ana & Teixeira, Ângelo Palos, 2022. "Enhancing capacity planning through forecasting: An integrated tool for maintenance of complex product systems," International Journal of Forecasting, Elsevier, vol. 38(1), pages 178-192.
  6. Beyca, Omer Faruk & Ervural, Beyzanur Cayir & Tatoglu, Ekrem & Ozuyar, Pinar Gokcin & Zaim, Selim, 2019. "Using machine learning tools for forecasting natural gas consumption in the province of Istanbul," Energy Economics, Elsevier, vol. 80(C), pages 937-949.
  7. Yang, Zhaoming & Liu, Zhe & Zhou, Jing & Song, Chaofan & Xiang, Qi & He, Qian & Hu, Jingjing & Faber, Michael H. & Zio, Enrico & Li, Zhenlin & Su, Huai & Zhang, Jinjun, 2023. "A graph neural network (GNN) method for assigning gas calorific values to natural gas pipeline networks," Energy, Elsevier, vol. 278(C).
  8. Du, Jian & Zheng, Jianqin & Liang, Yongtu & Wang, Bohong & Klemeš, Jiří Jaromír & Lu, Xinyi & Tu, Renfu & Liao, Qi & Xu, Ning & Xia, Yuheng, 2023. "A knowledge-enhanced graph-based temporal-spatial network for natural gas consumption prediction," Energy, Elsevier, vol. 263(PD).
  9. Kartikay Gupta & Niladri Chatterjee, 2021. "Stocks Recommendation from Large Datasets Using Important Company and Economic Indicators," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 667-689, December.
  10. Yu, Weichao & Huang, Weihe & Wen, Yunhao & Li, Yichen & Liu, Hongfei & Wen, Kai & Gong, Jing & Lu, Yanan, 2021. "An integrated gas supply reliability evaluation method of the large-scale and complex natural gas pipeline network based on demand-side analysis," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
  11. Ding, Jia & Zhao, Yuxuan & Jin, Junyang, 2023. "Forecasting natural gas consumption with multiple seasonal patterns," Applied Energy, Elsevier, vol. 337(C).
  12. Tomasz Cieślik & Piotr Narloch & Adam Szurlej & Krzysztof Kogut, 2022. "Indirect Impact of the COVID-19 Pandemic on Natural Gas Consumption by Commercial Consumers in a Selected City in Poland," Energies, MDPI, vol. 15(4), pages 1-18, February.
  13. Guoyou Yue, 2021. "A Review of the Research on Emergency Logistics for Tropical Cyclone Disasters in Guangxi," GATR Journals gjbssr591, Global Academy of Training and Research (GATR) Enterprise.
  14. Lu, Hongfang & Ma, Xin & Ma, Minda, 2021. "A hybrid multi-objective optimizer-based model for daily electricity demand prediction considering COVID-19," Energy, Elsevier, vol. 219(C).
  15. Jun Hao & Xiaolei Sun & Qianqian Feng, 2020. "A Novel Ensemble Approach for the Forecasting of Energy Demand Based on the Artificial Bee Colony Algorithm," Energies, MDPI, vol. 13(3), pages 1-25, January.
  16. Wei, Nan & Yin, Lihua & Li, Chao & Li, Changjun & Chan, Christine & Zeng, Fanhua, 2021. "Forecasting the daily natural gas consumption with an accurate white-box model," Energy, Elsevier, vol. 232(C).
  17. Jinyuan Liu & Shouxi Wang & Nan Wei & Yi Yang & Yihao Lv & Xu Wang & Fanhua Zeng, 2023. "An Enhancement Method Based on Long Short-Term Memory Neural Network for Short-Term Natural Gas Consumption Forecasting," Energies, MDPI, vol. 16(3), pages 1-14, January.
  18. Lu, Hongfang & Ma, Xin & Azimi, Mohammadamin, 2020. "US natural gas consumption prediction using an improved kernel-based nonlinear extension of the Arps decline model," Energy, Elsevier, vol. 194(C).
  19. Mostafavi, Seyed Alireza & Shirazi, Mohammad, 2020. "Thermal modeling of indirect water heater in city gate station of natural gas to evaluate efficiency and fuel consumption," Energy, Elsevier, vol. 212(C).
  20. Tsoumalis, Georgios I. & Bampos, Zafeirios N. & Chatzis, Georgios V. & Biskas, Pandelis N. & Keranidis, Stratos D., 2021. "Minimization of natural gas consumption of domestic boilers with convolutional, long-short term memory neural networks and genetic algorithm," Applied Energy, Elsevier, vol. 299(C).
  21. Razak Olu-Ajayi & Hafiz Alaka & Hakeem Owolabi & Lukman Akanbi & Sikiru Ganiyu, 2023. "Data-Driven Tools for Building Energy Consumption Prediction: A Review," Energies, MDPI, vol. 16(6), pages 1-20, March.
  22. Oleksandr Castello & Marina Resta, 2023. "A Machine-Learning-Based Approach for Natural Gas Futures Curve Modeling," Energies, MDPI, vol. 16(12), pages 1-22, June.
  23. Darya Pyatkina & Tamara Shcherbina & Vadim Samusenkov & Irina Razinkina & Mariusz Sroka, 2021. "Modeling and Management of Power Supply Enterprises’ Cash Flows," Energies, MDPI, vol. 14(4), pages 1-17, February.
  24. Alameer, Zakaria & Fathalla, Ahmed & Li, Kenli & Ye, Haiwang & Jianhua, Zhang, 2020. "Multistep-ahead forecasting of coal prices using a hybrid deep learning model," Resources Policy, Elsevier, vol. 65(C).
  25. K, Ashin Nishan M & ASHIQ, MUHAMMED V, 2019. "Role of Energy use in the Prediction of CO2 Emissions and Growth in India: An Application of Artificial Neural Networks (ANN)," SocArXiv gkpbu, Center for Open Science.
  26. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
  27. Ayşe Özmen, 2023. "Sparse regression modeling for short- and long‐term natural gas demand prediction," Annals of Operations Research, Springer, vol. 322(2), pages 921-946, March.
  28. Jason Runge & Radu Zmeureanu, 2019. "Forecasting Energy Use in Buildings Using Artificial Neural Networks: A Review," Energies, MDPI, vol. 12(17), pages 1-27, August.
  29. Bartłomiej Gaweł & Andrzej Paliński, 2024. "Global and Local Approaches for Forecasting of Long-Term Natural Gas Consumption in Poland Based on Hierarchical Short Time Series," Energies, MDPI, vol. 17(2), pages 1-25, January.
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