利用人工智能技术预测中国长江三角洲的空间分布和碳排放决定因素
Wen Zhang1, Weijun Yuan2, Wei Xuan3
1School of Architecture and Art, Hefei University of Technology, Hefei, 230009, China.
Scientific reports
|July 4, 2024
概括
这项研究使用人工智能预测中国长江三角洲的碳排放 (CE). 结果显示,CE将集中在工业区,并在经济增长的推动下,到2030年达到顶峰.
科学领域:
- 环境科学 环境科学
- 城市规划 城市规划
- 人工智能的人工智能
背景情况:
- 全球变暖需要有效的碳排放管理.
- 城市集群对空间规划和CE控制提出了复杂的挑战.
- 整合大数据和人工智能对于准确的CE分析至关重要.
研究的目的:
- 为城市CE开发一种人工智能驱动的空间分析方法.
- 准确分析当前的CE状态,并预测未来的长江三角洲 (YRD) 的空间分布.
- 确定CE的关键驱动因素,并为可持续的城市碳管理提供建议.
主要方法:
- 在CE上利用了多个来源的城市级空间时间大数据.
- 开发并应用了集成人工智能的优化空间分析方法.
- 采用先进的数据处理算法,提高准确性和可解释性.
主要成果:
- 开发的算法在YRD中实现了CE数据的0.93的高匹配精度.
- 从2025年到2030年,预计在"省资本带"和"重工业带"的高CE度.
- 确定经济基础是YRD中CE最重要的驱动因素,预测显示到2030年将达到峰值.
结论:
- 这种基于人工智能的方法为城市集群提供了准确的CE分析和预测.
- 结果为YRD中的有针对性的可持续城市碳管理策略提供了关键的见解.
- 该研究强调了经济因素在塑造未来碳排放趋势中的重要性.
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