Dr. Panga Narasimha Reddy, Dr. Bode Venkata Kavyatheja, Dr. B. Damodhara Reddy

Comparison of ANN and RSM in Predicting the Strength of Concrete

ARTIFICIAL NEURAL NETWORK (ANN) AND RESPONSE SURFACE METHODOLOGY (RSM) MODELS

• Broschiertes Buch

Produktbeschreibung

This study presents a comparative study between Artificial Neural Network (ANN) and Response Surface Methodology (RSM) in predicting the compressive strength of high strength concrete. The comparison was made based on the same experimental datasets. The inputs investigated in this study were percentage of Cement, Silica fume and coarse aggregate. The methods employed in ANN and RSM were feedforward neural network and face-centered central composite, correspondingly. The comparison between the two models showed that RSM performed better than ANN with coefficient of determination (R2) closer to 1 with 0.9959. In addition, all the predicted results by RSM against the experimental results fell within 10% margin. For ANN model, however, three of its predicted results were outside the 10% margin. Silica fume was also found to have greater impacts on the compressive strength of concrete than coarse aggregate.

Produktdetails

• Verlag: LAP Lambert Academic Publishing
• Seitenzahl: 68
• Erscheinungstermin: 10. Mai 2023
• Englisch
• Abmessung: 220mm x 150mm x 5mm
• Gewicht: 119g
• ISBN-13: 9786206163015
• ISBN-10: 6206163016
• Artikelnr.: 68165849

Autorenporträt

El Dr. P. Narasimha Reddy trabaja actualmente como profesor asistente en el Sri Venkateswara College of Engineering & Technology. Es Doctor en Filosofía por el Instituto Nacional de Tecnología de Srinagar (Jammu y Cachemira). Obtuvo su B.Tech (Ingeniería Civil) y M.Tech (Ingeniería Estructural) en JNTU Anantapur.