ARCEAK：一种结合建筑知识的自动化规则检查框架
ARCEAK: An Automated Rule Checking Framework Enhanced with Architectural Knowledge
AI总结：
本研究提出ARCEAK框架，将自动化规则检查分解为规则信息提取与验证代码生成两项任务，利用生成式预训练Transformer简化法规文本解释并自动生成检查代码，提升了建筑设计的合规性检查效率。
摘要：
自动化规则检查（ARC）通过解决行业专业人士进行的传统模型审查中繁琐、不一致且易出错的问题，在推动建筑业发展方面发挥着至关重要的作用。对照复杂的规则集进行人工评估通常会导致严重的项目延误和费用增加。为了应对这些挑战，ARC为提高建筑领域设计的效率和合规性提供了一个有前景的解决方案。然而，ARC的主要挑战在于将法规文本转换为适合计算机处理的格式。当前的规则解释方法需要大量的人工劳动，从而限制了其实用性。为了解决这个问题，我们的研究引入了一种新方法，将ARC分解为两个不同的任务：规则信息提取和验证代码生成。利用生成式预训练Transformer，我们的方法旨在简化法规文本的解释并简化模型合规性检查代码的生成过程。通过实证评估和案例研究，我们展示了我们的方法在自动化代码合规性检查中的有效性和潜力，提高了建设项目的效率和可靠性。
英文摘要：
Automated Rule Checking (ARC) plays a crucial role in advancing the construction industry by addressing the laborious, inconsistent, and error-prone nature of traditional model review conducted by industry professionals. Manual assessment against intricate sets of rules often leads to significant project delays and expenses. In response to these challenges, ARC offers a promising solution to improve efficiency and compliance in design within the construction sector. However, the main challenge of ARC lies in translating regulatory text into a format suitable for computer processing. Current methods for rule interpretation require extensive manual labor, thereby limiting their practicality. To address this issue, our study introduces a novel approach that decomposes ARC into two distinct tasks: rule information extraction and verification code generation. Leveraging generative pre-trained transformers, our method aims to streamline the interpretation of regulatory texts and simplify the process of generating model compliance checking code. Through empirical evaluation and case studies, we showcase the effectiveness and potential of our approach in automating code compliance checking, enhancing the efficiency and reliability of construction projects.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
