SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration
Data-driven models for predicting fire and explosion-related properties have been improved greatly in recent years using machine-learning algorithms. However, choosing the best machine learning approach is still a challenging task. Therefore, in this study, the predictability comparisons have been m...
| Main Authors: | Arshad, U., Taqvi, S.A.A., Buang, A., Awad, A. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.23830 / |
| Published: |
Institution of Chemical Engineers
2021
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108435212&doi=10.1016%2fj.psep.2021.06.001&partnerID=40&md5=8ddc80b7fd61d3d1878e84240682c584 http://eprints.utp.edu.my/23830/ |
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