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Concepts for improving machine learning based landslide assessment
(Springer Netherlands, 2019)
The main idea of this chapter is to address some of the key issues that were recognized in Machine Learning (ML) based Landslide Assessment Modeling (LAM). Through the experience of the authors, elaborated in several case ...
Axial Strength Prediction of Square CFST Columns Based on The ANN Model
(First Serbian International Conference on Applied Artificial Intelligence, Kragujevac, Serbia, 2022)
Due to numerous advantages, concrete-filled steel tubular (CFST) columns have an increasingly important role in the civil engineering industry. Because of the expensive experimental testing of these members, it is beneficial ...
Practical ANN prediction models for the axial capacity of square CFST columns
(Springer, 2023)
In this study, two machine-learning algorithms based on the artificial neural network
(ANN) model are proposed to estimate the ultimate compressive strength of square
concrete-filled steel tubular columns. The development ...
Prediction of Ultimate Compressive Strength of CCFT Columns Using Machine Learning Algorithms
(8th International Conference Science and Practice, Kolasin, Montenegro, 2022)
The composite concrete-filled steel tube columns are structural members with numerous advantages over the traditional reinforced concrete or the pure steel members. The behavior of these columns is highly nonlinear. This ...