The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 52-190
Full Name: Adel Abdollahzadeh
Position: Student
Age: ON
Sex: Male
Address: c220.taman tenaga.selangor-malaysia
Country: MALAYSIA
Tel: 0060172764002
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E-mail address: abdolahi@vlsi.eng.ukm.my
Other E-mails: abdollahi.adel@gmail.com
Title of the Paper: Predict Strength Of Rubberized Concrete Using Atrificial Neural Network
Authors as they appear in the Paper: A. ABDOLLAHZADEHa*,R.MASOUDNIAa, S. AGHABABAEIb
Email addresses of all the authors:
Number of paper pages: 10
Abstract: In this paper, behaviour of rubberized concrete was modelled using artificial neural network ANN and obtained results were compared to experimental data. Experimental test include recycling 5, 10, 15 and 20% percentage of concrete aggregate with different powder size 0.2, 0.4, 0.6, 0.8 mm of rubber. Results demonstrate high ability of ANN in Prediction of compressive strength of rubberized concrete compared to MLR (R2= 0.9650 and RMSE=0.017). Finally, the performance of each model was evaluated using the Root Mean Square Error (RMSE), Correlation Coefficient(R), Correlation of determination (R2), and Mean Absolute Relative Error (MARE).
Keywords: Rubberized concrete, Artificial neural network, Multi linear regression, Root Mean
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