Machine learning vs. ADM1: Reliable biogas prediction with minimal data requirements in full-scale plants
- DOI
- 10.1016/j.ese.2026.100662
- Published
- 2026-01
- Container
- Environmental Science and Ecotechnology
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.ese.2026.100662,
title = {Machine learning vs. ADM1: Reliable biogas prediction with minimal data requirements in full-scale plants},
author = {Sofia Tisocco and Sören Weinrich and Henrik Bjarne Møller and Alastair James Ward and Liam Kilmartin and Xinmin Zhan and Paul Crosson},
year = {2026},
journal = {Environmental Science and Ecotechnology},
doi = {10.1016/j.ese.2026.100662},
url = {https://doi.org/10.1016/j.ese.2026.100662}
}RIS
TY - JOUR TI - Machine learning vs. ADM1: Reliable biogas prediction with minimal data requirements in full-scale plants AU - Sofia Tisocco AU - Sören Weinrich AU - Henrik Bjarne Møller AU - Alastair James Ward AU - Liam Kilmartin AU - Xinmin Zhan AU - Paul Crosson PY - 2026 JO - Environmental Science and Ecotechnology DO - 10.1016/j.ese.2026.100662 UR - https://doi.org/10.1016/j.ese.2026.100662 ER -
APA
Tisocco, S., Weinrich, S., Møller, H. B., Ward, A. J., Kilmartin, L., Zhan, X., & Crosson, P. (2026). Machine learning vs. ADM1: Reliable biogas prediction with minimal data requirements in full-scale plants. Environmental Science and Ecotechnology. https://doi.org/10.1016/j.ese.2026.100662
Source records
- crossref · retrieved 2026-09-26T17:59:16.427Z