Two-Run Genetic Programming for Predicting Slump Flow of Concrete

Abstract:

A two-run genetic programming (GP) is proposed to estimate the slump flow of high-performance concrete (HPC) using several significant concrete ingredients in this study. GP optimizes functions and their associated coefficients simultaneously and is suitable to automatically discover relationships between nonlinear systems. Basic-GP usually suffers from premature convergence, which cannot acquire satisfying solutions and show satisfied performance only on low dimensional problems. Therefore it was improved by an automatically incremental procedure to improve the search ability and avoid local optimum. The results demonstrated that two-run GP generates an accurate formula through and has 7.5 % improvement on root mean squared error (RMSE) for predicting the slump flow of HPC than Basic-GP.

• Periodical: Applied Mechanics and Materials (Volume 590)
• Pages: 321-325
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.590.321
• Online since: June 2014
• Authors: Li Chen*, Chang Huan Kou, Kuan Ting Chen, Shih Wei Ma
• Keywords: Genetic Programming, High-Performance Concrete (HPC), Premature Convergence, Slump Flow

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