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Updated: Jun 13, 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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使用可解释的地理空间人工智能方法评估易受噪声污染的地区

Seyed Vahid Razavi-Termeh1, Abolghasem Sadeghi-Niaraki1, X Angela Yao2

  • 1Dept. of Computer Science & Engineering and Convergence Engineering for Intelligent Drone, XR Research Center, Sejong University, Seoul, Republic of Korea.

Journal of environmental management
|September 10, 2024
PubMed
概括

包括CatBoost-FA在内的地理空间人工智能 (GeoAI) 模型有效地绘制了德黑兰的噪音污染热点. CatBoost-FA模型在识别易受噪音污染的区域方面表现出卓越的准确性.

关键词:
可解释的人工智能地理空间的人工智能超启发式算法 (Metaheuristic Algorithms) 是一种算法,可以通过噪音污染 噪音污染 噪音污染在空间上是显式的.

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Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM12:26

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