Title of article :
High-performance concrete compressive strength prediction using Genetic Weighted Pyramid Operation Tree (GWPOT)
Author/Authors :
Cheng، نويسنده , , Min-Yuan and Firdausi، نويسنده , , Pratama Mahardika and Prayogo، نويسنده , , Doddy Zulverdi، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2014
Abstract :
This study uses the Genetic Weighted Pyramid Operation Tree (GWPOT) to build a model to solve the problem of predicting high-performance concrete compressive strength. GWPOT is a new improvement of the genetic operation tree that consists of the Genetic Algorithm, Weighted Operation Structure, and Pyramid Operation Tree. The developed model obtained better results in benchmark tests against several widely used artificial intelligence (AI) models, including the Artificial Neural Network (ANN), Support Vector Machine (SVM), and Evolutionary Support Vector Machine Inference Model (ESIM). Further, unlike competitor models that use “black-box” techniques, the proposed GWPOT model generates explicit formulas, which provide important advantages in practical application.
Keywords :
Concrete strength , genetic algorithm , Operation Tree , Weighted Pyramid Operation Tree , Prediction
Journal title :
Engineering Applications of Artificial Intelligence
Journal title :
Engineering Applications of Artificial Intelligence