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Energy economics
Technological forecasting & social change : an international journal
149
Springer eBook Collection
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NBER working paper series
135
Journal of business research : JBR
128
Pacific economic bulletin
117
International journal of production research
112
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Journal of the Academy of Marketing Science
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1
Machine learning and oil price point and density forecasting
Costa, Alexandre Bonnet R.
;
Ferreira, Pedro Cavalcanti
; …
- In:
Energy economics
102
(
2021
),
pp. 1-21
Persistent link: https://www.econbiz.de/10013162181
Saved in:
2
Predicting energy poverty with combinations of remote-sensing and socioeconomic survey data in India : evidence from machine learning
Wang, Hanjie
;
Maruejols, Lucie
;
Yu, Xiaohua
- In:
Energy economics
102
(
2021
),
pp. 1-13
Persistent link: https://www.econbiz.de/10013162202
Saved in:
3
Predicting corporate carbon footprints for climate finance risk analyses : a machine learning approach
Nguyen, Quyen
;
Diaz-Rainey, Ivan
;
Kuruppuarachchi, Duminda
- In:
Energy economics
95
(
2021
),
pp. 1-18
Persistent link: https://www.econbiz.de/10012816864
Saved in:
4
Won't get fooled again : a supervised machine learning approach for screening gasoline cartels
Silveira, Douglas
;
Vasconcelos, Silvinha Pinto
; …
- In:
Energy economics
105
(
2022
),
pp. 1-18
Persistent link: https://www.econbiz.de/10013201809
Saved in:
5
Machine learning in energy economics and finance: a review
Ghoddusi, Hamed
;
Creamer Guillén, Germán
;
Rafizadeh, Nima
- In:
Energy economics
81
(
2019
),
pp. 709-727
Persistent link: https://www.econbiz.de/10012172954
Saved in:
6
Using machine learning tools for forecasting natural gas consumption in the province of Istanbul
Beyca, Ömer Faruk
;
Ervural, Beyzanur Cayir
;
Tatoğlu, Ekrem
- In:
Energy economics
80
(
2019
),
pp. 937-949
Persistent link: https://www.econbiz.de/10012173755
Saved in:
7
Toward high-resolution projection of electricity prices : a machine learning approach to quantifying the effects of high fuel and CO2 prices
Madadkhani, Shiva
;
Ikonnikova, Svetlana
- In:
Energy economics
129
(
2024
),
pp. 1-18
Persistent link: https://www.econbiz.de/10014558952
Saved in:
8
Carbon emission efficiency of 284 cities in China based on machine learning approach : driving factors and regional heterogeneity
Xing, Peixue
;
Wang, Yanan
;
Ye, Tao
;
Sun, Ying
;
Li, Qiao
; …
- In:
Energy economics
129
(
2024
),
pp. 1-14
Persistent link: https://www.econbiz.de/10014559021
Saved in:
9
Environmental performance evaluation of electric enterprises during a power crisis : evidence from DEA methods and AI prediction algorithms
Pan, Yinghao
;
Zhang, Chao-Chao
;
Lee, Chien-chiang
;
Lv, …
- In:
Energy economics
130
(
2024
),
pp. 1-13
Persistent link: https://www.econbiz.de/10014559265
Saved in:
10
Forecasting the realized variance of oil-price returns using machine learning : is there a role for U.S. state-level uncertainty?
Çepni, Oğuzhan
;
Gupta, Rangan
;
Pienaar, Daniel
; …
- In:
Energy economics
114
(
2022
),
pp. 1-14
Persistent link: https://www.econbiz.de/10013477404
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