相关实验视频

Updated: May 27, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

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在印度东部的工业城市中,制定关于建地适合城市再生的评估决策框架

Harekrishna Manna1, Suraj Kumar Mallick2, Sanjit Sarkar3

  • 1Department of Geography, School of Earth Sciences, Central University of Karnataka, Kalaburagi, Karnataka, 585367, India. harekrishnamanna@gmail.com.

Scientific reports
|February 17, 2025
PubMed
概括

本研究使用机器学习确定了阿桑索尔市政公司城市发展的最佳地点. 主要发现突出了适合再生的区域,并为可持续规划策略提供了信息.

关键词:
构建的适用性 构建的适用性机器学习是机器学习.可持续发展目标 可持续发展目标城市增长 城市增长城市再生 城市再生

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Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm11:53

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

Published on: December 9, 2012

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