Predicting biodiesel properties and its optimal fatty acid profile via explainable machine learning
The accurate prediction of biodiesel fuel properties and determination of its optimal fatty acid (FA) profiles is a non-trivial process. To this aim, machine learning (ML) based predictive models were developed for cetane number (CN) and cold filter plugging point (CFPP), where the extreme gradient...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Elsevier
2022
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| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/33803/1/Predicting%20biodiesel%20properties%20and%20its%20optimal%20fatty%20acid%20profile%20via%20explainable%20machine%20learning.pdf https://eprints.ums.edu.my/id/eprint/33803/2/Predicting%20biodiesel%20properties%20and%20its%20optimal%20fatty%20acid%20profile%20via%20explainable%20machine%20learning1.pdf https://eprints.ums.edu.my/id/eprint/33803/ https://www.sciencedirect.com/science/article/pii/S0960148122002737?casa_token=jZDbLUKi4vAAAAAA:TMsOj_09hXypyKOx2c-DEzQUJK7b9HGwssbT15h3i2nVWNzbnNiiqK9ybWYMn_L6pvYxXOK3W6M https://doi.org/10.1016/j.renene.2022.02.124 |
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