| 书目名称 | Mathematical and Statistical Approaches for Anaerobic Digestion Feedstock Optimization |
| 编辑 | Federico Moretta,Giulia Bozzano |
| 视频video | |
| 概述 | Details the modeling of biomass blending for methane yield optimization.Uses machine learning techniques created with Python and Julia.Is a contribution to improving renewable energy technology |
| 丛书名称 | SpringerBriefs in Energy |
| 图书封面 |  |
| 描述 | .This book examines biomass mixture modeling and optimization. .The book discusses anaerobic digestion and related fermentative processes and explains their compositional dynamics. Early chapter examine macromolecules, elemental fractions, and their direct influence on methane production. Supported by an extensive data bank of substrates obtained from research, the book points out correlations that enable the estimation of global methane production for diverse biomass mixtures. Furthermore, it provides valuable insights into discerning the optimal composition capable of yielding the utmost methane output..The book integrates cutting-edge machine learning techniques and shows how the programming language Python and Julia can be used for analysis and to optimize processes. It has many graphs, figures, and visuals.. . . |
| 出版日期 | Book 2024 |
| 关键词 | Biomass Characterization; Anaerobic Digestion; Machine Learning; Database Management; Mathematical Model |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-56460-4 |
| isbn_softcover | 978-3-031-56459-8 |
| isbn_ebook | 978-3-031-56460-4Series ISSN 2191-5520 Series E-ISSN 2191-5539 |
| issn_series | 2191-5520 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 17:56:03
