Machine learning in energy economics and finance: A review
Abstract Machine learning (ML) is generating new opportunities for innovative research in
energy economics and finance. We critically review the burgeoning literature dedicated to …
energy economics and finance. We critically review the burgeoning literature dedicated to …
Hybrid structures in time series modeling and forecasting: A review
Z Hajirahimi, M Khashei - Engineering Applications of Artificial Intelligence, 2019 - Elsevier
The key factor in selecting appropriate forecasting model is accuracy. Given the deficiencies
of single models in processing various patterns and relationships latent in data, hybrid …
of single models in processing various patterns and relationships latent in data, hybrid …
Forecasting of future greenhouse gas emission trajectory for India using energy and economic indexes with various metaheuristic algorithms
The accelerating increment of greenhouse gas (GHG) concentration in the atmosphere
already reached an alarming level, and nowadays its adverse impacts on the living …
already reached an alarming level, and nowadays its adverse impacts on the living …
A hybrid algorithm for carbon dioxide emissions forecasting based on improved lion swarm optimizer
Global warming is a hot topic of climate change, and its negative impact on oceans, ecology,
and human health has become an indisputable fact. As a major cause of global warming …
and human health has become an indisputable fact. As a major cause of global warming …
Probing CO2 emission in Chengdu based on STRIPAT model and Tapio decoupling
F Yang, L Shi, L Gao - Sustainable Cities and Society, 2023 - Elsevier
Carbon dioxide (CO 2) is the primary driver of global warming. Conducting CO 2 emission
projections and identifying the decoupling relationship between CO 2 emission and …
projections and identifying the decoupling relationship between CO 2 emission and …
A review on machine learning forecasting growth trends and their real-time applications in different energy systems
T Ahmad, H Chen - Sustainable Cities and Society, 2020 - Elsevier
Energy forecasting and planning play an important role in energy sector development and
policy formulation. The forecasting model selection mostly based on the availability of the …
policy formulation. The forecasting model selection mostly based on the availability of the …
How can China achieve the 2030 carbon peak goal—a crossover analysis based on low-carbon economics and deep learning
C Shi, J Zhi, X Yao, H Zhang, Y Yu, Q Zeng, L Li… - Energy, 2023 - Elsevier
This paper studied the carbon peak through the cross-analysis of low-carbon economics
and deep learning. The STIRPAT model and ridge regression was used to distinguish and …
and deep learning. The STIRPAT model and ridge regression was used to distinguish and …
Research and application of association rule algorithm and an optimized grey model in carbon emissions forecasting
X Ma, P Jiang, Q Jiang - Technological Forecasting and Social Change, 2020 - Elsevier
Accurate carbon emissions forecasting plays a pivotal role in reducing global warming by
providing references to formulate emission reduction policies. Although numerous studies …
providing references to formulate emission reduction policies. Although numerous studies …
A bi-level reinforcement learning model for optimal scheduling and planning of battery energy storage considering uncertainty in the energy-sharing community
Sharing of battery energy storage systems (BESS) in the energy community by reflecting the
real world can play a significant role in achieving carbon neutrality. Therefore, this study …
real world can play a significant role in achieving carbon neutrality. Therefore, this study …
Energy-environmental-economic assessment of green retrofit policy to achieve 2050 carbon-neutrality in South Korea: Focused on residential buildings
To achieve carbon emission reduction target (CERT) by 2030 and carbon-neutrality in 2050,
it is important to actively reduce the emission gap in the private building sector. However, the …
it is important to actively reduce the emission gap in the private building sector. However, the …