Artificial neural networks applications in construction and building engineering (1991–2021): science mapping and visualization
Artificial neural network (ANN) has acquired noticeable interest from the research
community to handle complex problems in Construction and Building engineering (CB). This …
community to handle complex problems in Construction and Building engineering (CB). This …
Soil liquefaction mitigation in geotechnical engineering: An overview of recently developed methods
Triggered liquefaction in earthquakes, that soil displays fluid-like characteristics caused by
an on-going increase of pore water pressure and reduction of the effective stress, can …
an on-going increase of pore water pressure and reduction of the effective stress, can …
Design optimization of cement grouting material based on adaptive boosting algorithm and simplicial homology global optimization
J Ren, H Zhao, L Zhang, Z Zhao, Y Xu, Y Cheng… - Journal of Building …, 2022 - Elsevier
Cement grouting materials have been widely used in maintenance and reinforcement
engineering. Various design methods have been developed to determine the optimal …
engineering. Various design methods have been developed to determine the optimal …
Evaluating and predicting the stability of roadways in tunnelling and underground space using artificial neural network-based particle swarm optimization
In this study, a new technique for predicting roadways stability in tunneling and underground
space was proposed based on a combination of particle swarm optimization (PSO) …
space was proposed based on a combination of particle swarm optimization (PSO) …
[HTML][HTML] Empirical approach for prediction of bearing pressure of spread footings on clayey soil using artificial intelligence (AI) techniques
This study investigates the applicability of two artificial intelligence (AI) techniques, namely,
the support vector regression (SVR) and artificial neural network (ANN), in prediction of the …
the support vector regression (SVR) and artificial neural network (ANN), in prediction of the …
A hybrid computational intelligence approach for predicting soil shear strength for urban housing construction: a case study at Vinhomes Imperia project, Hai Phong …
This research proposes an alternative for estimating shear strength of soil based on a
hybridization of Support Vector Regression (SVR) and Particle Swarm Optimization (PSO) …
hybridization of Support Vector Regression (SVR) and Particle Swarm Optimization (PSO) …
An explainable intelligent algorithm for the multiple performance prediction of cement-based grouting materials
W Zhao, S Feng, J Liu, B Sun - Construction and Building Materials, 2023 - Elsevier
Cement-based grouting material, distinguished by excellent fluidity and high strength, is
widely used in the field of construction reinforcement, and anchoring of restraints. Owing to …
widely used in the field of construction reinforcement, and anchoring of restraints. Owing to …
[HTML][HTML] Exploring the effect of basalt fibers on maximum deviator stress and failure deformation of silty soils using ANN, SVM and FL supported by experimental data
Because the experimental trials in civil engineering field are difficult and time-consuming,
the application of artificial intelligence (AI) techniques is attracting considerable attention …
the application of artificial intelligence (AI) techniques is attracting considerable attention …
Hybrid grey wolf optimization algorithm–based support vector machine for groutability prediction of fractured rock mass
S Deng, X Wang, Y Zhu, F Lv, J Wang - Journal of Computing in …, 2019 - ascelibrary.org
Groutability determination is a very important task in grouting quality control. There is little
research on the groutability of cement-based grout in a fractured rock mass, and the …
research on the groutability of cement-based grout in a fractured rock mass, and the …
帷幕灌浆量区间预测的Bootstrap-IGWO-SVM 模型研究
李凯， 任炳昱， 关涛， 余佳， 王佳俊 - 水力发电学报, 2022 - slfdxb.cn
由于帷幕灌浆注灰量预测过程中存在地质参数, 预测模型和输入数据的不确定性,
传统的点预测结果存在误差, 并且难以对不确定性进行量化. 针对上述问题, 本研究提出基于 …
传统的点预测结果存在误差, 并且难以对不确定性进行量化. 针对上述问题, 本研究提出基于 …