Employing Genetic Programming and Regression Analysis to ReckonThePropertiesof High Performance Self Compacted Concrete: A Review

  • Vikas Khandelwal

Abstract

The High strength self compacting concrete’s strength and mechanical properties depends upon amount of parametric constituents used in the design of concrete. The IS code used for design of concrete usually takes number of trials to get the desired design methodology, by considering the effect on the strength of concrete that  every constituent particle does as per its volume/weight ratio. The actual strength of the final concrete usually varies by some percentage because the environmental conditions, material used and the method adopted for the design are not exactly as per standards. The ANN model does the same with number of trails being used for training, improving and finding out the hidden parameters for hidden ANN layers which affect the properties of the concrete in specific range. The ANN gives the final strength as per the environmental conditions in which the design was conducted, which plays an important factor the final strength and properties while the design of high strength self compacting concrete. The ANN model trained until the Root mean square value is less than 0.001 and errors are negligible. This study is conducted to develop the ANN model and to predict the compressive strength of high performance self compacting concrete in quite short period of time with minimum errors and without destructive laboratory tests.

Published
2020-06-01
How to Cite
Vikas Khandelwal. (2020). Employing Genetic Programming and Regression Analysis to ReckonThePropertiesof High Performance Self Compacted Concrete: A Review. International Journal of Advanced Science and Technology, 29(10s), 5291-5296. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/22173
Section
Articles