Bidirectional LSTM-Based Energy Consumption Forecasting: Advancing AI-Driven Cloud Integration for Cognitive City Energy Management
Efficient energy management is a cornerstone of advancing cognitive cities, where AI, IoT, and cloud computing seamlessly integrate to meet escalating global energy demands. Within this context, the ability to forecast electr... | Find, read and cite all the research you need on Tech Science Press
Authors
- Mohammad Tabrez Quasim (ORCID: https://orcid.org/0000-0002-5546-0405)
- S. Sheik Mohideen Shah
- Surbhi Bhatia (ORCID: https://orcid.org/0000-0003-3097-6568)
- Meganathan Selvamani
- Shakila Basheer (ORCID: https://orcid.org/0000-0001-9032-9560)
- Mahesh Thyluru Ramakrishna
- Wajdan Al Malwi
Publication Details
- Journal
- Computers, materials & continua/Computers, materials & continua (Print)
- Published
- 2025-01-01
- DOI
- https://doi.org/10.32604/cmc.2025.063809
- Citations
- 2
- Primary Topic
- Energy Load and Power Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 1.46