Predicting Shear Strength in FRP-Reinforced Concrete Beams Using Bat Algorithm-Based Artificial Neural Network

Application of Component-Based Mechanical Models and Artificial Intelligence to Bolted Beam-to-Column Connections

(2021) Iman Faridmehr et al.   Applied Sciences-Basel

Determining post-fire residual compressive strength of reinforced concrete shear walls using the BAT algorithm

(2021) Elham Shadbahr et al.   Structures

Modified imperialist competitive algorithm-based neural network to determine shear strength of concrete beams reinforced with FRP

(2020) Amir Hasanzade-Inallu et al.   Journal of Central South University

Evaluating the bond strength of FRP-to-concrete composite joints using metaheuristic-optimized least-squares support vector regression

(2020) Junfei Zhang et al.   NEURAL COMPUTING & APPLICATIONS

Computational parameter identification of strongest influence on the shear resistance of reinforced concrete beams by fiber reinforcement polymer

(2020) Yan Cao et al.   Structures

Shear capacity estimation of FRP-reinforced concrete beams using computational intelligence

(2020) Hosein Naderpour et al.   Structures

Shear strength prediction of FRP reinforced concrete members using generalized regression neural network

(2019) Md Shah Alam et al.   NEURAL COMPUTING & APPLICATIONS

Innovative models for prediction of compressive strength of FRP-confined circular reinforced concrete columns using soft computing methods

(2019) H. Naderpour et al.   COMPOSITE STRUCTURES

Shear strength prediction of reinforced concrete beams by baseline, ensemble, and hybrid machine learning models

(2019) Jui-Sheng Chou et al.   SOFT COMPUTING

A new formulation for prediction of the shear capacity of FRP in strengthened reinforced concrete beams

(2019) Reza Kamgar et al.   SOFT COMPUTING

Prediction of shear strength and behavior of RC beams strengthened with externally bonded FRP sheets using machine learning techniques

(2019) Omar R. Abuodeh et al.   COMPOSITE STRUCTURES

Prediction of FRP shear contribution for wrapped shear deficient RC beams using adaptive neuro-fuzzy inference system (ANFIS)

(2019) Swapnasarit Kar et al.   Structures

Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting

(2018) Mumtaz Ali et al.   ATMOSPHERIC RESEARCH

Shear resistance prediction of concrete beams reinforced by FRP bars using artificial neural networks

(2018) H. Naderpour et al.   MEASUREMENT

Experimental study on influence of proposed FRP-strengthening techniques on RC circular short columns considering different types of damage index

(2018) M. Haji et al.   COMPOSITE STRUCTURES

Optimized shear design equation for slender concrete beams reinforced with FRP bars and stirrups using Genetic Algorithm and reliability analysis

(2016) Md Shahnewaz et al.   ENGINEERING STRUCTURES

Application of artificial intelligence techniques to predict the performance of RC beams shear strengthened with NSM FRP rods. Formulation of design equations

(2014) Ricardo Perera et al.   COMPOSITES PART B-ENGINEERING

Shear strength of GFRP reinforced precast lightweight concrete panels

(2013) Ruifen Liu et al.   CONSTRUCTION AND BUILDING MATERIALS

Strength enhancement modeling of concrete cylinders confined with CFRP composites using artificial neural networks

(2012) Mostafa Jalal et al.   COMPOSITES PART B-ENGINEERING

An approach for estimating the capacity of RC beams strengthened in shear with FRP reinforcements using artificial neural networks

(2012) H.M. Tanarslan et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction of the ultimate strength of reinforced concrete beams FRP-strengthened in shear using neural networks

(2010) R. Perera et al.   COMPOSITES PART B-ENGINEERING

Genetic algorithm model for shear capacity of RC beams reinforced with externally bonded FRP

(2010) Moncef Nehdi et al.   MATERIALS AND STRUCTURES