江西省传统村庄的生态适应性评估基于使用人工智能的多模型集成
Cheng Zhang1,2, Jinlin Teng1,2, Peilin Liu1,2
1College of Landscape Architecture and Art, Jiangxi Agricultural University, Nanchang, China.
PloS one
|October 1, 2025
概括
传统村庄表现出高度的生态适应性,这是由于祖先在选址方面的智慧. 人工智能驱动的分析确定了诸如海拔和水域接近等关键因素,为江西省创建了一个适合性地图.
科学领域:
- 环境科学 环境科学
- 人工智能的人工智能
- 城市规划 城市规划
背景情况:
- 传统村庄具有很高的生态适应性,反映了祖先对环境适应和可持续性的理解.
- 从历史上看,选址的优先考虑是舒适,安全和生态和.
研究的目的:
- 通过基于人工智能的多模型整合方法,评估江西省传统村庄遗址的生态适用性.
- 确定影响祖先村庄选址的关键环境因素,并分析它们的生态智慧.
- 为江西省传统村庄生成生态适宜性评估地图.
主要方法:
- 利用环境数据 (地形,气候,息地质量,土地使用,空气质量,植被,河流网络) 和地理信息系统进行空间分析.
- 应用机器学习 (随机森林,SVM,GBDT) 和深度学习 (CNN,MLP) 模型.
- 集成多种模型以提高生态适宜性评估的准确性和稳定性.
主要成果:
- 确定了高度,斜率,息地质量,水的距离和平均温度作为村庄选址的主要因素.
- 人工智能多模型整合方法在评估生态适应性和确定关键因素方面表现出很高的表现.
- 一个复合适用性指数 (CSI) 被开发出来,并生成了一个生态适用性地图.
结论:
- 该研究验证了人工智能多模型集成对生态适应性评估的有效性.
- 这些发现为保护和发展传统村庄提供了科学基础.
- 该方法作为其他地区生态地点选择的参考.
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