Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Expert Systems with Applications: An International Journal
Using weighted genetic programming to program squat wall strengths and tune associated formulas
Engineering Applications of Artificial Intelligence
Aseismic ability estimation of school building using predictive data mining models
Expert Systems with Applications: An International Journal
A hybrid approach based on MEP and CSP for contour registration
Applied Soft Computing
A new predictive model for compressive strength of HPC using gene expression programming
Advances in Engineering Software
Expert Systems with Applications: An International Journal
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
Improving analytical models of circular concrete columns with genetic programming polynomials
Genetic Programming and Evolvable Machines
Engineering Applications of Artificial Intelligence
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This study proposed a novel knowledge discovery method, Genetic Operation Tree (GOT), which is composed of operation tree (OT) and genetic algorithm (GA), to automatically produce self-organized formulas to predict compressive strength of High-Performance Concrete. In GOT, OT plays the architecture to represent an explicit formula, and GA plays the optimization mechanism to optimize the OT to fit experimental data. Experimental data from several different sources were used to evaluate the method. The results showed that GOT can produce formulas which are more accurate than nonlinear regression formulas but less accurate than neural network models. However, neural networks are black box models, while GOT can produce explicit formulas, which is an important advantage in practical applications.