大型语言模型:为新的环境决策制定提供工具
1Graduate School of Environmental Science, Hokkaido University, Sapporo 060-0810, Japan.
Journal of environmental management
|February 2, 2025
概括
大型语言模型 (LLM) 可以帮助环境决策. 一个LLM辅助的方法增强人类的专业知识,以更好的水质管理,而LLM驱动的自动化面临的局限性在复杂的场景.
科学领域:
- 环境工程 环境工程
- 人工智能的人工智能
- 水资源管理 水资源管理
背景情况:
- 环境决策面临着复杂性和优化方面的挑战.
- 大型语言模型 (LLM) 提供了增强传统环境工作流程的潜力.
- 整合人工智能与环境模型需要仔细的框架设计.
研究的目的:
- 探索LLM在环境决策中的好处和局限性.
- 提出和比较两个框架:LLM辅助和LLM驱动.
- 使用水工程案例研究 (PFAS控制) 评估框架性能.
主要方法:
- 开发两个可通用的框架:LLM辅助和LLM驱动.
- 在使用环境流体动力学代码 (EFDC) 的水工程案例研究中应用框架.
- 在优化环境决策和管理PFAS污染方面评估框架性能.
主要成果:
- 两种LLM框架都有助于环境决策优化,在复杂的场景中具有不同的适用性.
- 该LLM辅助框架增强了PFAS拦截和流量调节的人类决策.
- 基于LLM的框架在复杂参数优化方面遇到了局限性,这是由于LLM的约束.
结论:
- 在环境决策方面,LLM可以增强,而不是取代人类的专业知识.
- 负责任的人类-人工智能合作对于优化环境管理至关重要.
- 该研究为将人工智能与传统环境建模集成奠定了基础.
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