AI賦能土木工程數(shù)值分析方法

專(zhuān)題介紹

人工智能Artificial Intelligence (AI) 是研究、開(kāi)發(fā)用于模擬、延伸和擴(kuò)展人的智能的理論、方法、技術(shù)及應(yīng)用系統(tǒng)的一門(mén)新的技術(shù)科學(xué)。人工智能是智能學(xué)科重要的組成部分，旨在了解智能的實(shí)質(zhì)，產(chǎn)生能以人類(lèi)智能相似的方式做出反應(yīng)的智能機(jī)器，該領(lǐng)域的研究包括機(jī)器人、語(yǔ)言識(shí)別、圖像識(shí)別、自然語(yǔ)言處理和專(zhuān)家系統(tǒng)等。人工智能從誕生以來(lái)，理論和技術(shù)日益成熟，應(yīng)用領(lǐng)域也不斷擴(kuò)大。

本專(zhuān)題介紹AI在土木工程領(lǐng)域數(shù)值分析方法相關(guān)的科學(xué)研究進(jìn)展，目前已錄用論文主題包括非線(xiàn)性不確定性量化全局靈敏度代理模型、非支配排序遺傳算法抗震措施優(yōu)化設(shè)計(jì)、松鼠搜索算法可持續(xù)混凝土抗壓強(qiáng)度預(yù)測(cè)、火災(zāi)條件下鋁合金節(jié)點(diǎn)網(wǎng)殼的數(shù)值分析等。

混凝土應(yīng)力數(shù)據(jù)分布圖（Enming LI, Ning ZHANG, Bin XI, Jian ZHOU, Xiaofeng GAO. Compressive strength prediction and optimization design of sustainable concrete based on squirrel search algorithm-extreme gradient boosting technique. Frontiers of Structural and Civil Engineering, 17(9), 1310-1325）

專(zhuān)題目錄
RESEARCH ARTICLENumerical analysis of aluminum alloy reticulated shells with gusset joints under fire conditionsShaojun ZHU, Zhangjianing CHENG, Chaozhong ZHANG, Xiaonong GUOFrontiers of Structural and Civil Engineering, 2023, 17(3): 448-466.https://doi.org/10.1007/s11709-022-0910-5RESEARCH ARTICLECompressive strength prediction and optimization design of sustainable concrete based on squirrel search algorithm-extreme gradient boosting techniqueEnming LI, Ning ZHANG, Bin XI, Jian ZHOU, Xiaofeng GAOFrontiers of Structural and Civil Engineering, 2023, 17(9): 1310-1325.https://doi.org/10.1007/s11709-023-0997-3RESEARCH ARTICLEOptimization design of anti-seismic engineering measures for intake tower based on non-dominated sorting genetic algorithm-IIJia’ao YU, Zhenzhong SHEN, Zhangxin HUANG, Haoxuan LIFrontiers of Structural and Civil Engineering, 2023, 17(9): 1428-1441.https://doi.org/10.1007/s11709-023-0998-2RESEARCH ARTICLEA surrogate model for uncertainty quantification and global sensitivity analysis of nonlinear large-scale dome structuresHuidong ZHANG, Yafei SONG, Xinqun ZHU, Yaqiang ZHANG, Hui WANG, Yingjun GAOhttps://doi.org/10.1007/s11709-023-0007-9(in press)