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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.
Autor: Kavyatheja, Bode Venkata Reddy, B. Damodhara Reddy, Panga Narasimha
ISBN: 9786206163015
Sprache: Englisch
Produktart: Kartoniert / Broschiert
Verlag: LAP Lambert Academic Publishing
Veröffentlicht: 10.05.2023
Untertitel: ARTIFICIAL NEURAL NETWORK (ANN) AND RESPONSE SURFACE METHODOLOGY (RSM) MODELS
Il Dr. P. Narasimha Reddy lavora attualmente come professore assistente presso lo Sri Venkateswara College of Engineering & Technology. Ha conseguito il dottorato di ricerca presso il National Institute of Technology di Srinagar (Jammu e Kashmir). Ha conseguito il B.Tech (Ingegneria civile) e il M.Tech (Ingegneria strutturale) presso il JNTU di Anantapur.