摘要
土木工程行业在信息化转型中面临着大量的非结构化的文本信息,大语言模型(large language models,LLMs)由于其强大的自然语言处理能力,为行业领域的智能化变革提供了新的机遇。采用系统性文献回顾的方法,在梳理LLMs的技术架构及在垂直领域研究现状的基础上,提出了LLMs在土木工程领域的四大应用场景及技术路线、面临的挑战及研究趋势。研究发现,LLMs已在土木工程领域有探索性的研究与应用,目前主要集中在内容生成类、智能问答类、文本摘要类及分析推理类四大应用场景,覆盖土木工程项目全生命周期阶段,并具有跨学科、跨模态融合的特性。然而,LLMs的应用仍面临知识专业性低、信息时效性差、数据质量及交互性低等挑战。基于此,提出了一系列未来研究机遇,在模型优化方面,利用参数高效微调技术注入专业知识,增强LLMs在土木工程领域应用的广度和深度;与知识图谱结合,提升LLMs在回答中的精准性、可解释性与时效性;融合多模态的数据类型,扩展LLMs在土木工程领域的应用场景;开发适用的模型评估方法,量化LLMs在土木工程领域应用的价值及性能表现。在应用场景方面,结合LLMs和土木工程领域特点,可以拓展LLMs在文档生成、问答系统、信息抽取、合规性审查等复杂任务中的应用,提高从业者与数据间的交互效率。研究旨在为学术界和企业界进一步将LLMs应用于土木工程领域提供借鉴与参考。
The civil engineering industry faces with a vast array of unstructured textual information during its digital transformation.Large language models(LLMs)provide a new opportunity for the intelligent transformation of the industry because of its powerful natural language processing capability.A systematic literature review approach was employed,and based on the technical framework of LLMs and the current state of research in vertical domains,four major application scenarios for LLMs in civil engineering were suggested,along with corresponding technological approaches,challenges faced,and research trends.It is found that exploratory research and application of LLMs in civil engineering have been conducted,primarily focusing on content creation,intelligent Q&A,text summarization,and analytical reasoning,covering the entire lifecycle of civil engineering projects and featuring interdisciplinary and multimodal integration.However,the utilization of LLMs struggles with low specificity of knowledge,poor timeliness of information,and inferior data quality and interactivity.Based on this,a series of future research opportunities were proposed to enhance the breadth and depth of LLMs application in the field of civil engineering by using parametric efficient fine-tuning technology to inject expertise in model optimization.Combined with knowledge graph,LLMs can improve the accuracy,interpretability and timeliness of answers.Multi-modal data types were integrated to expand the application scenarios of LLMs in civil engineering.Appropriate model evaluation methods were developed to quantify the value and performance of LLMs applications in civil engineering.In terms of application scenarios,combined with the characteristics of LLMs and civil engineering fields,the application of LLMs in complex tasks such as document generation,question and answer system,information extraction and compliance review can be expanded,and the interaction efficiency between practitioners and data can be improved.The purpose of the study is to provide reference for the academic and business circles to further apply LLMs in the field of civil engineering.
作者
许娜
陈曦
杨建平
张博
陈伟
XU Na;CHEN Xi;YANG Jian-ping;ZHANG Bo;CHEN Wei(School of Mechanics and Civil Engineering,China University of Mining and Technology,Xuzhou 221116,China;Artificial Intelligence Research Institute,China University of Mining and Technology,Xuzhou 221116,China;School of Civil Engineering,Xuzhou University of Technology,Xuzhou 221018,China;School of Computer Science&Technology,China University of Mining and Technology,Xuzhou 221116,China)
出处
《科学技术与工程》
北大核心
2025年第21期8773-8783,共11页
Science Technology and Engineering
基金
国家社会科学一般项目(23BGL277)。
关键词
土木工程
大语言模型
自然语言生成
生成式人工智能
civil engineering
large language models(LLMs)
natural language generation(NLG)
generative artificial intelligence(Gen-AI)
