Original paper

Interpretable machine learning for predicting and evaluating hydrogen production via supercritical water gasification of biomass

Volume: 316, Pages: 128244 - 128244
Published: Sep 1, 2021
Abstract
Supercritical water gasification (SCWG) of biomass for hydrogen production is a clean and promising technology. However, due to many factors involved in SCWG process, including biomass properties and process parameters, it is time consuming and capital intensive to evaluate the multi-dimensional relationship between them, as well as the hydrogen production capability using the experimental method. Therefore, it is necessary to develop an...
Paper Details
Title
Interpretable machine learning for predicting and evaluating hydrogen production via supercritical water gasification of biomass
Published Date
Sep 1, 2021
Volume
316
Pages
128244 - 128244
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