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Frontiers of Structural and Civil Engineering >> 2019, Volume 13, Issue 6 doi: 10.1007/s11709-019-0562-2
Predicting resilient modulus of recycled concrete and clay masonry blends for pavement applications using soft computing techniques
. Department of Civil and Environmental Engineering, Incheon National University, Incheon 22012, South Korea.. Incheon Disaster Prevention Research Center, Incheon National University, Incheon 22012, South Korea.. Department of Public Works and Civil Engineering, Mansoura University, Mansoura 35516, Egypt
Abstract
Keywords
Least Square Support Vector Machine ; Artificial Neural Network ; resilient modulus ; Recycled Concrete Aggregate ; Recycled Clay Masonry
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