Tam Derinlikli Esnek Üstyapıların Katman Özelliklerinin Tahmini İçin Lig Şampiyonası Algoritması

2020-03-01
This study proposes a backcalculation tool, based on the hybrid use of League Championship Algorithm (LCA) and Artificial Neural Network (ANN), in order to predict the stiffness related layer properties of full-depth asphalt pavements. The proposed algorithm, namely LCA-ANN, is composed of two main parts; (i) an ANN forward response model, which is developed with the nonlinear finite element solution, for computing the surface deflections, and (ii) LCA search algorithm which is employed to search and provide the best set of layer moduli to the ANN model. In order to evaluate the performance of the proposed method, a synthetically generated dataset and real field data are utilized. Moreover, to assess the searching ability of LCA, well-accepted metaheuristic algorithms; Simple Genetic Algorithm (SGA) and Particle Swarm Optimization (PSO) are employed for comparison purposes. Obtained results reveal that the proposed algorithm can predict the layer properties with a low order of error values and enables fast and reliable tool for backcalculation st
Mühendislik Bilimleri ve Tasarım Dergisi

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Citation Formats
O. Pekcan, “Tam Derinlikli Esnek Üstyapıların Katman Özelliklerinin Tahmini İçin Lig Şampiyonası Algoritması,” Mühendislik Bilimleri ve Tasarım Dergisi, pp. 273–284, 2020, Accessed: 00, 2021. [Online]. Available: https://dergipark.org.tr/tr/doi/10.21923/jesd.693743.