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Updated: May 21, 2025

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

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在Sungai Semenyih使用极端学习机器和元启发式优化方法预测悬浮沉积物负载

Azlan Saleh1, Mohd Asyraf Zulkifley2

  • 1Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi, 43600, Selangor, Malaysia; GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Gelugor, 11800, Penang, Malaysia.

Journal of environmental management
|March 18, 2025
PubMed
概括

这项研究使用极端学习机器 (ELM) 增强了悬浮沉积物负载 (SSL) 预测,并使用亨利气体可溶性优化 (HGSO) 进行了优化. 在精确的水资源和环境管理方面,ELM-HGSO被证明是最有效的.

关键词:
极端学习的机器学习.基于物理的优化优化.悬浮沉积物负载预测的预测

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