制造浪潮:一个概念框架,探索基于语言模型的大型多代理系统如何重塑水工程的概念框架
Seyed Hossein Hosseini1, Babak Zolghadr-Asli2, Henrikki Tenkanen1
1Department of Built Environment, School of Engineering, Aalto University, Espoo, Finland.
Water research
|December 25, 2025
概括
基于大型语言模型的多元代理 (LLM-MAs) 为复杂的水工程任务提供了新的解决方案. 这些智能系统增强了数据分析,建模和决策,以实现自适应和可追溯的水资源管理.
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:
- 水利工程在数据集成,分析,建模和决策方面面临着挑战.
- 在水利工程项目中,跨学科的合作至关重要,但往往很困难.
研究的目的:
- 探索基于大型语言模型的多代理 (LLM-MAs) 集成到水工程实践中.
- 确定LLM-MA如何支持和促进该领域的先进业务.
- 开发一个基础框架,以了解LLM-MAs在水利工程中的未来作用.
主要方法:
- 研究大型语言模型 (LLM) 的语言能力.
- 分析LLM-MA系统的模块化,可扩展和协作架构.
- 识别水利工程中的实际应用和潜在用例.
主要成果:
- 士学位可以为水工程挑战提供及时,适应性和可追溯的解决方案.
- 确定的应用包括压力下降检测,洪水管理和基于代理商的谈判以获得平衡的解决方案.
- 强调了LLM-MA在这个领域的能力和局限性.
结论:
- 法学士-士课程为提高水利工程的效率和有效性提供了一个有希望的途径.
- 为成功实施LLM-MAs在现场提出了实际建议.
- 这项研究为人工智能驱动的水利工程未来的研究和开发奠定了基础.
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