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Original Articles

Determining structural strength of existing asphalt layer using condition survey data

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Pages 603-611 | Received 09 May 2011, Accepted 16 Mar 2012, Published online: 12 Apr 2012

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Vidhi Vyas, Ajit Pratap Singh & Anshuman Srivastava. (2021) Prediction of asphalt pavement condition using FWD deflection basin parameters and artificial neural networks. Road Materials and Pavement Design 22:12, pages 2748-2766.
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Irvin Pinto & Ashley Buss. (2020) Layer coefficients of cold in-place recycled layers from performance data. International Journal of Pavement Engineering 21:3, pages 304-310.
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Articles from other publishers (5)

Sushmita Bhandari, Xiaohua Luo & Feng Wang. (2023) Understanding the effects of structural factors and traffic loading on flexible pavement performance. International Journal of Transportation Science and Technology 12:1, pages 258-272.
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Mansour Fakhri & Reza Shahni Dezfoulian. (2019) Pavement structural evaluation based on roughness and surface distress survey using neural network model. Construction and Building Materials 204, pages 768-780.
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Gaetano Bosurgi, Orazio Pellegrino & Giuseppe Sollazzo. (2019) Optimizing Artificial Neural Networks For The Evaluation Of Asphalt Pavement Structural Performance. The Baltic Journal of Road and Bridge Engineering 14:1, pages 58-79.
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Zia Uddin Ahmed Zihan, Mostafa A. Elseifi, Kevin Gaspard & Zhongjie Zhang. (2018) Development of a Structural Capacity Prediction Model Based on Traffic Speed Deflectometer Measurements. Transportation Research Record: Journal of the Transportation Research Board 2672:40, pages 315-325.
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Omar ElbagalatiMostafa A. ElseifiKevin GaspardZhongjie Zhang. (2017) Development of an artificial neural network model to predict subgrade resilient modulus from continuous deflection testing. Canadian Journal of Civil Engineering 44:9, pages 700-706.
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