Journal ArticleDOI
A modified firefly algorithm-artificial neural network expert system for predicting compressive and tensile strength of high-performance concrete
Reads0
Chats0
TLDR
The result indicates that the MFA-ANN hybrid system can obtain a better prediction of the high-performance concrete properties and can provide an efficient and accurate tool to predict and design HPC.About:
This article is published in Construction and Building Materials.The article was published on 2018-08-20. It has received 187 citations till now. The article focuses on the topics: Firefly algorithm & Expert system.read more
Citations
More filters
Journal ArticleDOI
Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer
TL;DR: The hybridization of the models with GWO improves the training and generalization capability of both ANN and ANFIS models and it is deduced that ANN models trained with Levenberg-Marquardt algorithm outperformed other ANN-based models as well as all ANfIS- based models.
Journal ArticleDOI
Machine learning prediction of mechanical properties of concrete: Critical review
TL;DR: Examination of several Machine Learning models for forecasting the mechanical properties of concrete, including artificial neural networks, support vector machine, decision trees, and evolutionary algorithms are examined.
Journal ArticleDOI
Predicting the compressive strength of silica fume concrete using hybrid artificial neural network with multi-objective grey wolves
TL;DR: Estimating the compressive strength of silica fume concrete using the ANN method was considered as a two-objective optimization problem, and an ANN model with just one hidden layer with five neurons and the Pearson correlation coefficient of 0.9617 was chosen as the final ANN model.
Journal ArticleDOI
Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete.
TL;DR: Two artificial intelligence approaches, namely adaptive neuro fuzzy inference (ANFIS) and artificial neural network (ANN), were used to predict the compressive strength of GPC, where coarse and fine waste steel slag were used as aggregates.
Journal ArticleDOI
A generalized method to predict the compressive strength of high-performance concrete by improved random forest algorithm
TL;DR: The proposed method with two stages to select proper variables, simplify parameter settings, and predict HPCCS shows a strong generalization capacity, and the prediction performance of the model is better when the input variables are expressed as absolute mass.
References
More filters
Journal ArticleDOI
A method for the solution of certain non – linear problems in least squares
TL;DR: In this article, the problem of least square problems with non-linear normal equations is solved by an extension of the standard method which insures improvement of the initial solution, which can also be considered an extension to Newton's method.
Book
Pattern Recognition and Machine Learning (Information Science and Statistics)
TL;DR: Looking for competent reading resources?
Journal ArticleDOI
On the performance of artificial bee colony (ABC) algorithm
Dervis Karaboga,Bahriye Basturk +1 more
TL;DR: The simulation results show that the performance of ABC algorithm is comparable to those of differential evolution, particle swarm optimization and evolutionary algorithm and can be efficiently employed to solve engineering problems with high dimensionality.
Journal ArticleDOI
Cracking particles: A simplified meshfree method for arbitrary evolving cracks
Timon Rabczuk,Ted Belytschko +1 more
TL;DR: A new approach for modelling discrete cracks in meshfree methods is described, in which the crack can be arbitrarily oriented, but its growth is represented discretely by activation of crack surfaces at individual particles, so no representation of the crack's topology is needed.