Musa, Wahab and Katili, Muhammad Rifai and Ridwan, Wrastawa (2025) Optimizing Machine Learning Architectures for Time Series Forecasting: A Hybrid rvGA-eNM Approach. EAI Endorsed Transactions on AI and Robotics.
![[thumbnail of 79735.pdf]](http://eprints.eai.eu/style/images/fileicons/application_pdf.png "79735.pdf")
PDF
79735.pdf
Download (2MB)
Abstract
This study introduces a hybrid rvGA-eNM (real-valued Genetic Algorithm with enhanced Nelder-Mead) optimization approach for time series forecasting, specifically designed to address data scarcity and computational efficiency challenges in operational environments. Unlike contemporary hybrid algorith
| Item Type: | Article |
|---|---|
| Date Deposited: | 04 Mar 2026 20:21 |
| Last Modified: | 10 Apr 2026 17:45 |
| URI: | http://eprints.eai.eu/id/eprint/60342 |
Actions (login required)
- View Item