机器学习在生物酒精生产和利用中的机制,方法和应用:一篇综述
Chen Wang1, Xuemeng Zhang1, Guohua Zhao2
1State Key Laboratory of Pollution Control and Resources Reuse, School of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China.
Chemosphere
|September 16, 2023
概括
机器学习 (ML) 为推进生物酒精提供了强大的工具. 这次审查详细介绍了MLML的细节.
科学领域:
- 可再生能源和化学工程 化学工程
背景情况:
- 生物酒精是化石燃料的关键替代品.
- 机器学习 (ML) 在生物酒精研究中越来越重要.
- 了解ML应用对于生物燃料的发展至关重要.
研究的目的:
- 审查生物酒精领域的ML机制,方法和应用.
- 突出ML在生物甲醇和生物乙醇生产中的作用.
- 引导使用ML以优化生物燃料利用和减少排放.
主要方法:
- 审查ML工作流程,强调问题定义和功能工程.
- 对各种ML模型及其适用于生物酒精应用的分析.
- 检查ML对生物甲醇生产 (热解,气化) 和生物乙醇发酵的影响.
主要成果:
- 在生物酒精中的预测和优化任务中,ML是有效的.
- 特定的ML方法适用于不同的生物酒精生产阶段.
- ML有助于优化发动机性能和减少生物酒精的排放.
结论:
- ML显著简化了生物酒精领域的研究和开发.
- 这一审查为将ML应用于生物燃料挑战提供了一个框架.
- ML对整个生物燃料行业具有巨大的潜力.
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