一个多目标优化框架,它包含可解释的CatBoost和修改的粘液模具算法,以解决炉燃烧优化问题

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

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Shan Gao1, Yunpeng Ma1

  • 1School of Information Engineering, Tianjin University of Commerce, Beichen, Tianjin 300134, China.

Biomimetics (Basel, Switzerland)
|November 26, 2024
PubMed
概括

这项研究引入了一个AI框架,用于优化循环流化床炉,将热效率提高0.68%,并将NOx排放量减少37.55%. 该方法有效地建模和优化复杂的燃烧系统.

关键词:
炉燃烧的优化 炉燃烧的优化可以解释的CatBoost CatBoost多目标优化框架.粘液模具算法 粘液模具算法

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