Block structure optimization in PEMFC flow channels using a data-driven surrogate model based on random forest

Research article (International Journal of Green Energy, 2022) · cited 17× · AI/ML
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Block structure optimization in PEMFC flow channels using a data-driven surrogate model based on random forest

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Block structure optimization in PEMFC flow channels using a data-driven surrogate model based on random forest is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Block structure optimization in PEMFC flow channels using a data-driven surrogate model based on random forest. Retrieved May 24, 2026, from https://4ort.xyz/entity/block-structure-optimization-in-pemfc-flow-channels-using-a-data-driven-surrogate-model-based-on-random-forest
MLA “Block structure optimization in PEMFC flow channels using a data-driven surrogate model based on random forest.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/block-structure-optimization-in-pemfc-flow-channels-using-a-data-driven-surrogate-model-based-on-random-forest.
BibTeX @misc{4ortxyz_block-structure-optimization-in-pemfc-flow-channels-using-a-data-driven-surrogate-model-based-on-random-forest_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Block structure optimization in PEMFC flow channels using a data-driven surrogate model based on random forest}}, year = {2026}, url = {https://4ort.xyz/entity/block-structure-optimization-in-pemfc-flow-channels-using-a-data-driven-surrogate-model-based-on-random-forest}, note = {Accessed: 2026-05-24}}
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