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Updated: Jun 6, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
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Published on: July 24, 2016

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通过基于改进的DRASTIC方法的机器学习模型提高地下水资源质量预测

Ali Bakhtiarizadeh1, Mohammad Najafzadeh2, Sedigheh Mohamadi3

  • 1Department of Water Engineering, Faculty of Civil and Surveying Engineering, Graduate University of Advanced Technology, Kerman, 76315117, Iran.

Scientific reports
|December 2, 2024
PubMed
概括

这项研究评估了Kerman-Baghin的地下水脆弱性,使用软计算方法预测酸盐脆弱性指数 (NVI). 进化多项式回归 (EPR) 显示出最佳表现,确定大多数地区的地下水脆弱性非常低至低.

关键词:
人工智能模型的人工智能模型这是极端的,极端的.地下水资源 地下水资源土地使用情况 土地使用情况酸盐污染 污染 酸盐污染

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