Efficient training of two ANNs using four meta-heuristic algorithms for predicting the FRP strength
A Kaveh, N Khavaninzadeh - Structures, 2023 - Elsevier
In recent years, artificial neural network (ANN) is one of the popular and effective machine
learning models that can be used to accurately predict fiber reinforced polymer (FRP) …
learning models that can be used to accurately predict fiber reinforced polymer (FRP) …
Predicting behavior of FRP-confined concrete using neuro fuzzy, neural network, multivariate adaptive regression splines and M5 model tree techniques
This paper studies the ability of artificial neural network (ANN), adaptive neuro fuzzy
inference system (ANFIS), multivariate adaptive regression splines (MARS) and M5 Model …
inference system (ANFIS), multivariate adaptive regression splines (MARS) and M5 Model …
Evaluating the bond strength of FRP in concrete samples using machine learning methods
In recent years, the use of Fiber Reinforced Polymers (FRPs) as one of the most common
ways to increase the strength of concrete samples, has been introduced. Evaluation of the …
ways to increase the strength of concrete samples, has been introduced. Evaluation of the …
Prediction of concrete compressive strength: Research on hybrid models genetic based algorithms and ANFIS
Z Yuan, LN Wang, X Ji - Advances in Engineering Software, 2014 - Elsevier
The management of concrete quality is an important task of concrete industry. This paper
researched on the structured and unstructured factors which affect the concrete quality …
researched on the structured and unstructured factors which affect the concrete quality …
[HTML][HTML] Artificial neural network for predicting the flexural bond strength of FRP bars in concrete
MA Köroğlu - Science and Engineering of Composite Materials, 2019 - degruyter.com
The bond strength between fibre-reinforced polymer (FRP) rebars and concrete is one of the
most significant aspects of composite behaviour for rebars and concrete. In this study, a …
most significant aspects of composite behaviour for rebars and concrete. In this study, a …
Prediction compressive strength of concrete containing GGBFS using random forest model
Improvement of compressive strength prediction accuracy for concrete is crucial and is
considered a challenging task to reduce costly experiments and time. Particularly, the …
considered a challenging task to reduce costly experiments and time. Particularly, the …
Intelligent prediction modeling for flexural capacity of FRP-strengthened reinforced concrete beams using machine learning algorithms
Fiber-reinforced polymers (FRP) are widely utilized to improve the efficiency and durability of
concrete structures, either through external bonding or internal reinforcement. However, the …
concrete structures, either through external bonding or internal reinforcement. However, the …
Ensemble tree-based approach towards flexural strength prediction of frp reinforced concrete beams
Due to rise in infrastructure development and demand for seawater and sea sand concrete,
fiber-reinforced polymer (FRP) rebars are widely used in the construction industry. Flexural …
fiber-reinforced polymer (FRP) rebars are widely used in the construction industry. Flexural …
Ensemble learning based approach for FRP-concrete bond strength prediction
SZ Chen, SY Zhang, WS Han, G Wu - Construction and Building Materials, 2021 - Elsevier
Nowadays, externally bonding fiber reinforced polymer (FRP) plates or sheets have become
a major maintenance approach for aged reinforced concrete flexure structures. However, the …
a major maintenance approach for aged reinforced concrete flexure structures. However, the …
A modified firefly algorithm-artificial neural network expert system for predicting compressive and tensile strength of high-performance concrete
The compressive and tensile strength of high-performance concrete (HPC) is a highly
nonlinear function of its constituents. The significance of expert frameworks for predicting the …
nonlinear function of its constituents. The significance of expert frameworks for predicting the …