Konu "Machine learning" için İnşaat Mühendisliği Bölümü Koleksiyonu listeleme
Toplam kayıt 8, listelenen: 1-8
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Data-driven ensemble learning approach for optimal design of cantilever soldier pile retaining walls
(Elsevier, 2023)Cantilever soldier pile retaining walls are used to ensure the stability of excavations. This paper deploys ensemble machine learning algorithms towards achieving optimum design of these structures. A large dataset was ... -
Data-driven interpretable ensemble learning methods for the prediction of wind turbine power incorporating SHAP analysis
(Elsevier, 2023)Wind energy increasingly attracts investment from many countries as a clean and renewable energy source. Since wind energy investment cost is high, the efficiency of a potential wind power plant should be determined ... -
Explainable data-driven ensemble learning models for the mechanical properties prediction of concrete confined by aramid fiber-reinforced polymer wraps using generative adversarial networks
(2023): The current study offers a data-driven methodology to predict the ultimate strain and compressive strength of concrete reinforced by aramid FRP wraps. An experimental database was collected from the literature, on which ... -
Explainable machine learning model for predicting punching shear strength of FRC flat slabs
(Elsevier BV, 2023)Reinforced concrete slabs are vulnerable to punching shear failure at the slab-column joint, which can initiate catastrophic progressive collapse. The addition of steel fibers in the concrete matrix has emerged as an ... -
Interpretable predictive modelling of basalt fiber reinforced concrete splitting tensile strength using ensemble machine learning methods and SHAP approach
(2023)Basalt fibers are a type of reinforcing fiber that can be added to concrete to improve its strength, durability, resistance to cracking, and overall performance. The addition of basalt fibers with high tensile strength ... -
Neural network predictive models for alkali-activated concrete carbon emission using metaheuristic optimization algorithms
(2023)Due to environmental impacts and the need for energy efficiency, the cement industry aims to make more durable and sustainable materials with less energy requirements without compromising mechanical properties based on ... -
Optimal dimensions of post-tensioned concrete cylindrical walls using harmony search and snsemble learning with SHAP
(2023)The optimal design of prestressed concrete cylindrical walls is greatly beneficial for economic and environmental impact. However, the lack of the available big enough datasets for the training of robust machine learning ... -
Predictive modeling of recycled aggregate concrete beam shear strength using explainable ensemble learning methods
(2023)Construction and demolition waste (CDW) together with the pollution caused by the production of new concrete are increasingly becoming a burden on the environment. An appealing strategy from both an ecological and a ...