کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1758683 | 1523208 | 2015 | 11 صفحه PDF | دانلود رایگان |
• Ultrasonic pulse velocity prediction based on series of pulse velocity tests.
• Various mixtures of cement content and peat content for different curing period.
• Simulates the ultrasonic pulse velocity with adaptive neuro-fuzzy inference system.
• Adaptive neuro fuzzy application.
Ultrasonic pulse velocity is affected by defects in material structure. This study applied soft computing techniques to predict the ultrasonic pulse velocity for various peats and cement content mixtures for several curing periods. First, this investigation constructed a process to simulate the ultrasonic pulse velocity with adaptive neuro-fuzzy inference system. Then, an ANFIS network with neurons was developed. The input and output layers consisted of four and one neurons, respectively. The four inputs were cement, peat, sand content (%) and curing period (days). The simulation results showed efficient performance of the proposed system. The ANFIS and experimental results were compared through the coefficient of determination and root-mean-square error. In conclusion, use of ANFIS network enhances prediction and generation of strength. The simulation results confirmed the effectiveness of the suggested strategies.
Journal: Ultrasonics - Volume 61, August 2015, Pages 103–113