Improve carbon dioxide emission prediction in the Asia and Oceania (OECD): nature-inspired optimisation algorithms versus conventional machine learning,Engineering Applications of Computational Fluid Mechanics

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Improve carbon dioxide emission prediction in the Asia and Oceania (OECD): nature-inspired optimisation algorithms versus conventional machine learning
Engineering Applications of Computational Fluid Mechanics ( IF 5.9 ) Pub Date : 2024-08-23 , DOI: 10.1080/19942060.2024.2391988
Loke Kok Foong _{1,

2} , Vojtech Blazek ₃ , Lukas Prokop ₃ , Stanislav Misak ₃ , Farruh Atamurotov _{4,

5,

6} , Nima Khalilpoor ₇

Affiliation

This paper investigates the application of three nature-inspired optimisation algorithms – SHO, MFO, and GOA – combined with four machine learning methods – Gaussian Processes, Linear Regression, M...

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