人工智能算法在智能建造中的应用分析
Analysis of the Application of Artificial Intelligence Algorithms in Intelligent Construction
摘要: 当前，随着人工智能的迅速发展，传统土木工程学科已逐渐朝向智能建造方向发展。这对土木工程学科及行业领域都带来了新的变化，对行业从业人员的知识及技能储备也提出了更高的要求，行业领域与前沿科学技术间的联系越来越紧密，各类相关算法及模型的应用与发展都对土木工程行业的智能化发展起到了明显的推动作用。本文着重分析人工智能算法的科学技术方法论，探讨人工智能模式下智能建造的应用，以及算法模型对智能建造所带来的行业变革。
Abstract: At present, with the rapid development of artificial intelligence, the traditional civil engineering discipline has gradually developed towards intelligent construction. The artificial intelligence has brought new changes to the civil engineering, and has put forward higher requirements for the knowledge and skill reserve of industry practitioners. The connection between the industry and cutting-edge science and technology has become closer and closer. The application of various related algorithms and models have played a significant role in promoting the intelligent development of the civil engineering industry. This paper focuses on the analysis of the scientific and technological methodology of artificial intelligence algorithms, discusses the application of intelligent construction under artificial intelligence mode, and discusses the industry changes brought by algorithm models to intelligent construction.
文章引用：林庆吾. 人工智能算法在智能建造中的应用分析[J]. 交叉科学快报, 2024, 8(3): 379-384. https://doi.org/10.12677/isl.2024.83047

参考文献

[1] 柴天佑. 工业人工智能发展方向[J]. 自动化学报, 2020, 46(10): 2005-2012.
[2] 欧斌, 吴邦彬, 袁杰, 等. 基于LSTM的混凝土坝变形预测模型[J]. 水利水电科技进展, 2022, 42(1): 21-26.
[3] Knyazeva, N., Nazojkin, E. and Orekhov, A. (2023) The Use of Artificial Intelligence to Detect Defects in Building Structures. Construction and Architecture, 11, 18. [Google Scholar] [CrossRef] 
[4] 楚荣珍, 周向宁, 李顺刚. 人工神经网络及在建筑施工中应用[J]. 工业建筑, 2006(S1): 962-964.
[5] 匡建超, 徐志英. 偏最小二乘神经网络在建筑造价预测中的应用[J]. 商业研究, 2006(17): 88-91.
[6] 王勃, 崔洋, 董丽欣. 基于随机森林算法的高层建筑机械拆除方法判断[J]. 低温建筑技术, 2020, 42(12): 40-42.
[7] 李明海, 刘敏. 基于人工鱼群神经网络算法的建筑能耗预测[J]. 现代建筑电气, 2016, 7(3): 28-32.
[8] 罗钏雯. 基于粒子群优化算法的算法实现及建筑生形——模拟鸟类觅食形态的建筑雏形设计[J]. 华中建筑, 2020, 38(2): 43-47.
[9] 黄骞. 基于离散萤火虫算法的轨道交通车站建筑内部空间设计优化[J]. 科技和产业, 2023, 23(22): 119-122.
[10] 韩臻, 张颀, 刘刚. 人工免疫算法在建筑照明改造中的应用[J]. 照明工程学报, 2019, 30(2): 103-108.
[11] 郑杰, 吴世永, 毕小青. 人工智能在建筑行业的应用分析[J]. 中国市场, 2019(35): 54-58.
[12] Cha, Y., Choi, W. and Büyüköztürk, O. (2017) Deep Learning‐Based Crack Damage Detection Using Convolutional Neural Networks. Computer-Aided Civil and Infrastructure Engineering, 32, 361-378. [Google Scholar] [CrossRef] 
[13] Behzadan, A.H., Aziz, Z., Anumba, C.J. and Kamat, V.R. (2008) Ubiquitous Location Tracking for Context-Specific Information Delivery on Construction Sites. Automation in Construction, 17, 737-748. [Google Scholar] [CrossRef] 
[14] 鞠松, 杨晓东. 国内外人工智能技术在建筑行业的研究与应用现状[J]. 价值工程, 2018, 37(4): 225-228.
[15] 毛超, 彭窑胭. 智能建造的理论框架与核心逻辑构建[J]. 工程管理学报, 2020, 34(5): 1-6.
[16] 连晓燕. 浅析自然辩证法对城市智慧化管理的指导作用[J]. 现代经济信息, 2018(10): 55-56.