AIGC技术在水利工程设计中的应用前景与挑战

Prospects and challenges of AIGC technology in hydraulic engineering design

摘要

人工智能生成内容(AIGC)技术，结合人工智能与生成式计算，通过机器学习、深度神经网络和生成式模型等方法，从海量数据中提取要素，生成复杂内容，为各领域带来颠覆性变革。在水利工程设计领域，AIGC技术展现出广阔前景，如高精度流量预测、智能水资源管理、流域综合治理及全生命周期设计智能化等。然而，其应用亦面临诸多挑战，如工程项目独特性、算法适用性、数据质量参差不齐、基础设施不完善、人才培养滞后及信息安全问题等。为应对这些挑战，需持续推动跨学科技术创新，加强行业数据积累与分析，培养引进专业人才，构建高素质技术团队。期望通过这些努力，充分发挥AIGC技术在水利工程设计智能化、精细化和可持续发展中的变革作用，为水利工程未来发展注入新活力。

Abstract

Artificial Intelligence Generated Content(AIGC) technology, as an emerging field combining artificial intelligence with generative computation, is rapidly evolving through method such as machine learning, deep neural networks, and generative models. It extracts elements from massive datasets and generates complex content, bringing disruptive transformations to numerous sectors. In the domain of hydraulic engineering design, AIGC technology demonstrates extensive potential applications. These include high-precision river flow predictions based on Long Short-Term Memory(LSTM) neural networks, intelligent water resource management and integrated basin governance using machine learning algorithms, and enabling the entire lifecycle design of hydraulic projects through intelligent systems. However, the unique nature of engineering projects, algorithm applicability, data quality, infrastructure development, talent cultivation, and information security also pose significant challenges to the application of AIGC technology in hydraulic engineering design. Continuous interdisciplinary technological innovation, industry data accumulation, and professional talent development are crucial in addressing these challenges, facilitating the transformative role of AIGC technology in promoting intelligent, refined, and sustainable development in hydraulic engineering design.

关键词

AIGC技术 / 水利工程 / 数字化 / 创新发展

Key words

AIGC technology / hydraulic engineering / digitalization / innovative development

Author summay

李宇星(1994—), 男, 工程师, 学士, 从事水工设计研究和BIM 设计工作。E-mail: [e-mail]