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Evaluating the impact of the COVID-19 pandemic on the geospatial distribution of buildings' carbon footprints associated with electricity consumption
Zaidan, Esmat
;
Abulibdeh, Ammar
;
Jabbar, Rateb
;
Onat, …
- In:
Energy strategy reviews
52
(
2024
),
pp. 1-22
CF model predictions by employing three distinct
machine-learning
models
. Spatial analyses were conducted to identify …
Persistent link: https://www.econbiz.de/10014583312
Saved in:
2
Urban-regional disparities in mental health signals in Australia during the COVID-19 pandemic : a study via Twitter data and
machine
learning
models
Wang, Siqing
;
Zhang, Mengxi
;
Huang, Xiao
;
Hu, Tao
;
Li, …
- In:
Cambridge journal of regions, economy and society
15
(
2022
)
3
,
pp. 663-682
Persistent link: https://www.econbiz.de/10013541727
Saved in:
3
The impact of liquidity conditions on the time-varying link between U.S. municipal green bonds and major risky markets during the COVID-19 crisis : a machine learning approach
Kocaarslan, Baris
;
Mushtaq, Rizwan
- In:
Energy policy : the international journal of the …
184
(
2024
),
pp. 1-15
Persistent link: https://www.econbiz.de/10014454919
Saved in:
4
The role of major markets in predicting the US municipal green bond market performance : new evidence from
machine
learning
models
Kocaarslan, Baris
;
Soytaş, Uǧur
- In:
Technological forecasting & social change : an …
196
(
2023
),
pp. 1-14
Persistent link: https://www.econbiz.de/10014476443
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