Samira Hasanzadeh

Personal Details

First Name:	Samira
Middle Name:
Last Name:	Hasanzadeh
Suffix:
RePEc Short-ID:	pha1360
	[This author has chosen not to make the email address public]
	https://www.samirahasanzadeh.com/

Affiliation

Department of Business and Economics
Huron University College
University of Western Ontario

London, Canada
https://huronatwestern.ca/programs/arts-social-science/economics/
RePEc:edi:hcuwoca (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Samira Hasanzadeh & Hashmat Khan, 2016. "Sources of Canadian Economic Growth," Carleton Economic Papers 16-02, Carleton University, Department of Economics, revised 16 Oct 2017.
   • Samira Hasanzadeh & Hashmat Khan, 2019. "Sources of Canadian economic growth," Canadian Journal of Economics, Canadian Economics Association, vol. 52(1), pages 279-302, February.
   • Samira Hasanzadeh & Hashmat Khan, 2019. "Sources of Canadian economic growth," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 52(1), pages 279-302, February.

   Cited by:

   1. Daping Zhao & Sajid Anwar & W. Robert J. Alexander, 2022. "Sources of economic slowdown: A simultaneous equations approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2549-2565, April.

Articles

1. Samira Hasanzadeh & Hashmat Khan, 2019. "Sources of Canadian economic growth," Canadian Journal of Economics, Canadian Economics Association, vol. 52(1), pages 279-302, February.
   • Samira Hasanzadeh & Hashmat Khan, 2019. "Sources of Canadian economic growth," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 52(1), pages 279-302, February.
   • Samira Hasanzadeh & Hashmat Khan, 2016. "Sources of Canadian Economic Growth," Carleton Economic Papers 16-02, Carleton University, Department of Economics, revised 16 Oct 2017.
   See citations under working paper version above.
2. Forouzanfar, Mehdi & Doustmohammadi, A. & Hasanzadeh, Samira & Shakouri G, H., 2012. "Transport energy demand forecast using multi-level genetic programming," Applied Energy, Elsevier, vol. 91(1), pages 496-503.

   Cited by:

   1. Li, Zheng & Zhou, Bo & Hensher, David A., 2022. "Forecasting automobile gasoline demand in Australia using machine learning-based regression," Energy, Elsevier, vol. 239(PD).
   2. Ekaterina Grushevenko, 2015. "Complex method of petroleum products demand forecasting considering economic, demographic and technological factors," Economics and Business Letters, Oviedo University Press, vol. 4(3), pages 98-107.
   3. Jian Chai & Shubin Wang & Shouyang Wang & Ju’e Guo, 2012. "Demand Forecast of Petroleum Product Consumption in the Chinese Transportation Industry," Energies, MDPI, vol. 5(3), pages 1-22, March.
   4. 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.
   5. Tatiana Mitrova & Vyacheslav Kulagin & Dmitry Grushevenko & Ekaterina Grushevenko, 2015. "Technological Innovation as a Factor of Demand for Energy Sources in Automotive Industry," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 9(4), pages 18-31.
   6. Ben Jebli, Mehdi & Ben Youssef, Slim, 2013. "Output, renewable and non-renewable energy consumption and international trade: Evidence from a panel of 69 countries," MPRA Paper 56494, University Library of Munich, Germany, revised 07 Apr 2014.
      • Ben Jebli, Mehdi & Ben Youssef, Slim, 2015. "Output, renewable and non-renewable energy consumption and international trade: Evidence from a panel of 69 countries," Renewable Energy, Elsevier, vol. 83(C), pages 799-808.
   7. Abdulkerim Karaaslan & Mesliha Gezen, 2017. "Forecasting of Turkey s Sectoral Energy Demand by Using Fuzzy Grey Regression Model," International Journal of Energy Economics and Policy, Econjournals, vol. 7(1), pages 67-77.

3. Forouzanfar, Mehdi & Doustmohammadi, Ali & Menhaj, M. Bagher & Hasanzadeh, Samira, 2010. "Modeling and estimation of the natural gas consumption for residential and commercial sectors in Iran," Applied Energy, Elsevier, vol. 87(1), pages 268-274, January.

   Cited by:

   1. Yukseltan, Ergun & Yucekaya, Ahmet & Bilge, Ayse Humeyra & Agca Aktunc, Esra, 2021. "Forecasting models for daily natural gas consumption considering periodic variations and demand segregation," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
   2. Song, Jiancai & Zhang, Liyi & Jiang, Qingling & Ma, Yunpeng & Zhang, Xinxin & Xue, Guixiang & Shen, Xingliang & Wu, Xiangdong, 2022. "Estimate the daily consumption of natural gas in district heating system based on a hybrid seasonal decomposition and temporal convolutional network model," Applied Energy, Elsevier, vol. 309(C).
   3. Li, Junchen & Dong, Xiucheng & Shangguan, Jianxin & Hook, Mikael, 2011. "Forecasting the growth of China’s natural gas consumption," Energy, Elsevier, vol. 36(3), pages 1380-1385.
   4. 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.
   5. Szoplik, Jolanta, 2015. "Forecasting of natural gas consumption with artificial neural networks," Energy, Elsevier, vol. 85(C), pages 208-220.
   6. Seyed Azad Nabavi & Alireza Aslani & Martha A. Zaidan & Majid Zandi & Sahar Mohammadi & Naser Hossein Motlagh, 2020. "Machine Learning Modeling for Energy Consumption of Residential and Commercial Sectors," Energies, MDPI, vol. 13(19), pages 1-22, October.
   7. Jean Gaston Tamba & Salom Ndjakomo Essiane & Emmanuel Flavian Sapnken & Francis Djanna Koffi & Jean Luc Nsouand l & Bozidar Soldo & Donatien Njomo, 2018. "Forecasting Natural Gas: A Literature Survey," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 216-249.
   8. Marta P. Fernandes & Joaquim L. Viegas & Susana M. Vieira & João M. C. Sousa, 2017. "Segmentation of Residential Gas Consumers Using Clustering Analysis," Energies, MDPI, vol. 10(12), pages 1-26, December.
   9. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
   10. Jiang, Weiheng & Wu, Xiaogang & Gong, Yi & Yu, Wanxin & Zhong, Xinhui, 2020. "Holt–Winters smoothing enhanced by fruit fly optimization algorithm to forecast monthly electricity consumption," Energy, Elsevier, vol. 193(C).
   11. Forouzanfar, Mehdi & Doustmohammadi, A. & Hasanzadeh, Samira & Shakouri G, H., 2012. "Transport energy demand forecast using multi-level genetic programming," Applied Energy, Elsevier, vol. 91(1), pages 496-503.
   12. Adedayo Ajayi & Patrick Chi-Kwong Luk & Liyun Lao & Mohammad Farhan Khan, 2023. "Energy Forecasting Model for Ground Movement Operation in Green Airport," Energies, MDPI, vol. 16(13), pages 1-19, June.
   13. Huebner, Gesche M. & Hamilton, Ian & Chalabi, Zaid & Shipworth, David & Oreszczyn, Tadj, 2015. "Explaining domestic energy consumption – The comparative contribution of building factors, socio-demographics, behaviours and attitudes," Applied Energy, Elsevier, vol. 159(C), pages 589-600.
   14. Soldo, Božidar, 2012. "Forecasting natural gas consumption," Applied Energy, Elsevier, vol. 92(C), pages 26-37.
   15. Ravnik, J. & Hriberšek, M., 2019. "A method for natural gas forecasting and preliminary allocation based on unique standard natural gas consumption profiles," Energy, Elsevier, vol. 180(C), pages 149-162.
   16. Spoladore, Alessandro & Borelli, Davide & Devia, Francesco & Mora, Flavio & Schenone, Corrado, 2016. "Model for forecasting residential heat demand based on natural gas consumption and energy performance indicators," Applied Energy, Elsevier, vol. 182(C), pages 488-499.
   17. Rehman, Aniqa & Zhu, Jun-Jie & Segovia, Javier & Anderson, Paul R., 2022. "Assessment of deep learning and classical statistical methods on forecasting hourly natural gas demand at multiple sites in Spain," Energy, Elsevier, vol. 244(PA).
   18. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
   19. Potočnik, Primož & Soldo, Božidar & Šimunović, Goran & Šarić, Tomislav & Jeromen, Andrej & Govekar, Edvard, 2014. "Comparison of static and adaptive models for short-term residential natural gas forecasting in Croatia," Applied Energy, Elsevier, vol. 129(C), pages 94-103.
   20. Harris, Tyler M. & Devkota, Jay P. & Khanna, Vikas & Eranki, Pragnya L. & Landis, Amy E., 2018. "Logistic growth curve modeling of US energy production and consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 46-57.
   21. Wang, Jianzhou & Jiang, Haiyan & Zhou, Qingping & Wu, Jie & Qin, Shanshan, 2016. "China’s natural gas production and consumption analysis based on the multicycle Hubbert model and rolling Grey model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1149-1167.
   22. Reza Hafezi & Amir Naser Akhavan & Mazdak Zamani & Saeed Pakseresht & Shahaboddin Shamshirband, 2019. "Developing a Data Mining Based Model to Extract Predictor Factors in Energy Systems: Application of Global Natural Gas Demand," Energies, MDPI, vol. 12(21), pages 1-22, October.
   23. Guo-Feng Fan & An Wang & Wei-Chiang Hong, 2018. "Combining Grey Model and Self-Adapting Intelligent Grey Model with Genetic Algorithm and Annual Share Changes in Natural Gas Demand Forecasting," Energies, MDPI, vol. 11(7), pages 1-21, June.
   24. Amin Yousefi-Sahzabi & Kyuro Sasaki & Hossein Yousefi & Yuichi Sugai, 2011. "CO 2 emission and economic growth of Iran," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 16(1), pages 63-82, January.
   25. Melikoglu, Mehmet, 2013. "Vision 2023: Forecasting Turkey's natural gas demand between 2013 and 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 393-400.
   26. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
   27. Payne, James E. & Loomis, David G. & Wilson, Renardo, 2011. "Residential Natural Gas Demand in Illinois: Evidence from the ARDL Bounds Testing Approach," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 41(2), pages 1-10.
   28. Bianco, Vincenzo & Scarpa, Federico & Tagliafico, Luca A., 2014. "Scenario analysis of nonresidential natural gas consumption in Italy," Applied Energy, Elsevier, vol. 113(C), pages 392-403.
   29. Ahmad, Tanveer & Zhang, Hongcai, 2020. "Novel deep supervised ML models with feature selection approach for large-scale utilities and buildings short and medium-term load requirement forecasts," Energy, Elsevier, vol. 209(C).
   30. Askari, S. & Montazerin, N. & Fazel Zarandi, M.H., 2016. "Gas networks simulation from disaggregation of low frequency nodal gas consumption," Energy, Elsevier, vol. 112(C), pages 1286-1298.
   31. Ahmad, Tanveer & Huanxin, Chen & Zhang, Dongdong & Zhang, Hongcai, 2020. "Smart energy forecasting strategy with four machine learning models for climate-sensitive and non-climate sensitive conditions," Energy, Elsevier, vol. 198(C).
   32. Ergun Yukseltan & Ahmet Yucekaya & Ayse Humeyra Bilge & Esra Agca Aktunc, 2020. "Forecasting Models for Daily Natural Gas Consumption Considering Periodic Variations and Demand Segregation," Papers 2003.13385, arXiv.org.
   33. Shoaib Ahmed Khatri & Nayyar Hussain Mirjat & Khanji Harijan & Mohammad Aslam Uqaili & Syed Feroz Shah & Pervez Hameed Shaikh & Laveet Kumar, 2022. "An Overview of the Current Energy Situation of Pakistan and the Way Forward towards Green Energy Implementation," Energies, MDPI, vol. 16(1), pages 1-27, December.
   34. Li, Fengyun & Zheng, Haofeng & Li, Xingmei & Yang, Fei, 2021. "Day-ahead city natural gas load forecasting based on decomposition-fusion technique and diversified ensemble learning model," Applied Energy, Elsevier, vol. 303(C).
   35. Azadeh, A. & Asadzadeh, S.M. & Saberi, M. & Nadimi, V. & Tajvidi, A. & Sheikalishahi, M., 2011. "A Neuro-fuzzy-stochastic frontier analysis approach for long-term natural gas consumption forecasting and behavior analysis: The cases of Bahrain, Saudi Arabia, Syria, and UAE," Applied Energy, Elsevier, vol. 88(11), pages 3850-3859.
   36. 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.
   37. Karadede, Yusuf & Ozdemir, Gultekin & Aydemir, Erdal, 2017. "Breeder hybrid algorithm approach for natural gas demand forecasting model," Energy, Elsevier, vol. 141(C), pages 1269-1284.

More information

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-INO: Innovation (2) 2016-03-29 2017-07-23
2. NEP-EFF: Efficiency and Productivity (1) 2017-07-23
3. NEP-FDG: Financial Development and Growth (1) 2016-03-29
4. NEP-GRO: Economic Growth (1) 2016-03-29
5. NEP-HEA: Health Economics (1) 2020-09-28
6. NEP-KNM: Knowledge Management and Knowledge Economy (1) 2017-07-23
7. NEP-SBM: Small Business Management (1) 2016-03-29

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