Carbon emission price point-interval forecasting based on multivariate variational mode decomposition and attention-LSTM model

Zeng, Liling; Hu, Huanling; Tang, Huajun; Zhang, Xuejing; Zhang, Dabin

doi:10.1016/j.asoc.2024.111543

Applied Soft Computing

2024

DOI: 10.1016/j.asoc.2024.111543

|View full text |Cite

Carbon emission price point-interval forecasting based on multivariate variational mode decomposition and attention-LSTM model

Liling Zeng,

Huanling Hu,

Huajun Tang

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A new framework for ultra-short-term electricity load forecasting model using IVMD–SGMD two–layer decomposition and INGO–BiLSTM–TPA–TCN

Cui,

Zhang,

Niu

2024

Applied Soft Computing

View full text Add to dashboard Cite

A new framework for ultra-short-term electricity load forecasting model using IVMD–SGMD two–layer decomposition and INGO–BiLSTM–TPA–TCN

Cui,

Zhang,

Niu

2024

Applied Soft Computing

View full text Add to dashboard Cite

An adaptive photovoltaic power interval prediction based on multi-objective optimization

Jiang,

Wang,

Yang

et al. 2024

Computers and Electrical Engineering

View full text Add to dashboard Cite

Forecasting bitcoin: Decomposition aided long short-term memory based time series modeling and its explanation with Shapley values

Mizdrakovic,

Kljajic,

Zivkovic

et al. 2024

Knowledge-Based Systems

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Carbon emission price point-interval forecasting based on multivariate variational mode decomposition and attention-LSTM model

Cited by 3 publications

References 52 publications

A new framework for ultra-short-term electricity load forecasting model using IVMD–SGMD two–layer decomposition and INGO–BiLSTM–TPA–TCN

A new framework for ultra-short-term electricity load forecasting model using IVMD–SGMD two–layer decomposition and INGO–BiLSTM–TPA–TCN

An adaptive photovoltaic power interval prediction based on multi-objective optimization

Forecasting bitcoin: Decomposition aided long short-term memory based time series modeling and its explanation with Shapley values

Contact Info

Product

Resources

About