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Stiffness Performance Of Polyethylene Terephthalate Modified Asphalt Mixtures Estimation Using Support Vector Machine-Firefly Algorithm

Faculty of Engineering University of Malaya

Predicting asphalt pavement performance is an important matter which can save cost and energy. To ensure an accurate estimation of performance of the mixtures, new soft computing techniques can be used. In this study, in order to estimate the stiffness property of Polyethylene Terephthalate (PET) modified asphalt mixture, different soft computing methods were developed, namely: support vector machine-firefly algorithm (SVM-FFA), genetic programming (GP), artificial neural network (ANN) and support vector machine. The support vector machine-firefly algorithm (SVM-FFA) is a metaheuristic search algorithm developed according to the socially dashing manners of fireflies in nature. To develop the models, experiments were performed. …