环境评估的生成人工智能:可持续性分析的新范式
Syed Masiur Rahman1,2,3, Asif Raihan4, Shadi Abudalfa5,6
1Department of Civil and Environmental Engineering, King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia.
Environmental management
|February 9, 2026
概括
生成型人工智能 (GenAI) 为环境评估和可持续性提供了动态方法. 这篇评论探讨了GenAI的研究.
科学领域:
- 环境科学与可持续发展
- 人工智能和机器学习
- 环境管理环境管理
背景情况:
- 传统的环境评估模型往往是静态的和有限的.
- 新兴的生成人工智能 (GenAI) 提出了动态和参与式环境管理的新范式.
- 基因人工智能集成了数据合成,场景建模和治理见解.
研究的目的:
- 综合审查GenAI在环境评估和可持续性分析中的新兴角色.
- 识别和分析关键的GenAI架构及其在环境环境中的应用.
- 提出一个框架,以确保GenAI在环境管理中的负责任实施.
主要方法:
- 使用CIMO框架进行系统文献综述 (SLR).
- 分析了182个学术和技术出版物 (2015-2025年).
- 综合生成对抗网络 (GAN),变异自编码器 (VAE),大型语言模型 (LLM) 和扩散模型的发展.
主要成果:
- 在解决数据稀缺问题,提高模型可扩展性和促进参与决策方面,GenAI显示出潜力.
- 关键应用包括合成数据生成,场景模拟,遥感,预测分析和公众参与.
- 发现的挑战包括可解释性,数据偏差,验证,环境足迹和道德治理.
结论:
- 基因人工智能可以显著提升环境评估和可持续性分析.
- 负责任的整合需要一个三层框架,重点是技术忠实性,透明度和治理.
- 有效实施需要混合建模,参与式数据治理和可持续的人工智能基础设施,以实现透明度,问责制和公平.
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