MyJournals Home  

RSS FeedsMaterials, Vol. 12, Pages 3708: Learned Prediction of Compressive Strength of GGBFS Concrete Using Hybrid Artificial Neural Network Models (Materials)

 
 

10 november 2019 17:00:19

 
Materials, Vol. 12, Pages 3708: Learned Prediction of Compressive Strength of GGBFS Concrete Using Hybrid Artificial Neural Network Models (Materials)
 




A new hybrid intelligent model was developed for estimating the compressive strength (CS) of ground granulated blast furnace slag (GGBFS) concrete, and the synergistic benefits of the hybrid algorithm as compared with a single algorithm were verified. While using the collected 269 data from previous experimental studies, artificial neural network (ANN) models with three different learning algorithms namely back-propagation (BP), particle swarm optimization (PSO), and new hybrid PSO-BP algorithms, were constructed and the performance of the models was evaluated with regard to the prediction accuracy, efficiency, and stability through a threefold procedure. It was found that the PSO-BP neural network model was superior to the simple ANNs that were trained by a single algorithm and it is suitable for predicting the CS of GGBFS concrete.


Del.icio.us Digg Facebook Google StumbleUpon Twitter
 
48 viewsCategory: Chemistry, Physics
 
Materials, Vol. 12, Pages 3709: Reduced Graphene Oxides Decorated NiSe Nanoparticles as High Performance Electrodes for Na/Li Storage (Materials)
Materials, Vol. 12, Pages 3707: Measurements of Forces and Selected Surface Layer Properties of AW-7075 Aluminum Alloy Used in the Aviation Industry after Abrasive Machining (Materials)
 
 
blog comments powered by Disqus


MyJournals.org
The latest issues of all your favorite science journals on one page

Username:
Password:

Register | Retrieve

Search:

Physics

Use these buttons to bookmark us:
Del.icio.us Digg Facebook Google StumbleUpon Twitter


Valid HTML 4.01 Transitional
Copyright © 2008 - 2019 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Travel Photos Nachrichten Indigonet Finances Leer Mandarijn