Amanote Research
Register
Sign In
Predicting Compressive Strength of Recycled Concrete for Construction 3D Printing Based on Statistical Analysis of Various Neural Networks
Journal of Building Construction and Planning Research
doi 10.4236/jbcpr.2018.62005
Full Text
Open PDF
Abstract
Available in
full text
Date
January 1, 2018
Authors
Kang Tan
Publisher
Scientific Research Publishing, Inc,
Related search
Experimental Study on the Cubic Compressive Strength of Recycled Sand Concrete
DEStech Transactions on Materials Science and Engineering
Predictive Model for Compressive Strength of Concrete Made From Recycled Concrete Coarse Aggregates
Nigerian Journal of Technology
Using Artificial Neural Networks Approach to Estimate Compressive Strength for Rubberized Concrete
Periodica Polytechnica: Civil Engineering
Civil
Geotechnical Engineering
Engineering Geology
Structural Engineering
Study on Compressive Strength of Plastic Waste Bituminous Concrete for Road Construction
Nauchno-tekhnicheskiy vestnik Bryanskogo gosudarstvennogo universiteta
Statistical Analysis on Concrete Strength
Modern Civil and Structural Engineering
Probabilistic Modelling of Compressive Strength of Concrete Using Response Surface Methodology and Neural Networks
Arabian Journal for Science and Engineering
Multidisciplinary
Various Testing Conditions Affecting Measured Compressive Strength of Concrete
Concrete Journal
Virtual Revision on Compressive Srength of Conventional Concrete and Recycled Aggregate Concrete Consisting Treated Recycled Aggregate
International Journal of Recent Technology and Engineering
Engineering
Management of Technology
Innovation
Performance Comparison of SVM and ANN in Predicting Compressive Strength of Concrete
IOSR Journal of Computer Engineering