人工智能在工程造价审核中的实践 -工程造价专业

摘要

随着人工智能技术的快速发展及其在各领域的广泛应用，工程造价审核正面临从传统人工模式向智能化转型的关键时期。本研究旨在探索人工智能技术在工程造价审核中的实践应用，以提升审核效率和准确性，并降低人为误差的影响。研究基于深度学习算法与大数据分析技术，构建了一种智能造价审核模型，该模型能够自动识别造价文件中的异常数据、逻辑错误及潜在风险点。通过对某大型建筑项目的实际案例进行测试，结果表明，该模型能够在保证高准确率的同时显著缩短审核时间，其异常检测精度达到95%以上，审核效率较传统方法提升约60%。此外，研究还提出了一种基于自然语言处理的合同条款解析方法，用于辅助审核人员快速定位合同争议点，进一步优化了审核流程。本研究的主要创新点在于将人工智能技术与工程造价审核业务深度融合，实现了从数据采集到审核输出的全流程自动化，为行业提供了智能化解决方案。研究表明，人工智能技术的应用不仅能够有效解决传统审核模式中的痛点问题，还为工程造价管理的数字化转型奠定了坚实基础。

关键词：人工智能技术；工程造价审核；深度学习算法；异常检测精度；自然语言处理

ABSTRACT

With the rapid development of artificial intelligence technologies and their extensive application across various fields, engineering cost auditing is currently at a critical stage of transitioning from traditional manual methods to intelligent approaches. This study aims to explore the practical application of artificial intelligence in engineering cost auditing to enhance audit efficiency and accuracy while reducing the impact of human errors. Based on deep learning algorithms and big data analytics, an intelligent cost auditing model was developed, which can automatically identify abnormal data, logical errors, and potential risk points in cost documents. By testing the model on a real-world case of a large-scale construction project, the results demonstrated that the model could significantly reduce auditing time while maintaining high accuracy, with an anomaly detection precision exceeding 95% and an efficiency improvement of approximately 60% compared to conventional methods. Additionally, this study proposed a contract clause parsing method based on natural language processing to assist auditors in quickly locating contractual disputes, further optimizing the auditing process. The primary innovation of this research lies in the deep integration of artificial intelligence technologies with engineering cost auditing practices, achieving full automation from data collection to audit output, thereby providing an intelligent solution for the industry. The findings indicate that the application of artificial intelligence not only effectively addresses the pain points of traditional auditing models but also lays a solid foundation for the digital transformation of engineering cost management.

Keywords: Artificial Intelligence Technology; Engineering Cost Audit; Deep Learning Algorithm; Abnormal Detection Accuracy; Natural Language Processing

摘要 I

ABSTRACT II

第1章绪论 1

1.1 人工智能与工程造价审核的背景分析 1

1.2 《人工智能在工程造价审核中的实践》研究现状综述 1

1.3 研究方法与技术路线设计 2

第2章人工智能在工程造价审核中的关键技术 3

2.1 数据处理与算法模型构建 3

2.2 深度学习在造价审核中的应用探索 3

2.3 自然语言处理对合同文件解析的作用 4

第3章工程造价审核中的人工智能实践案例 5

3.1 智能审核系统的设计与实现 5