RETRACTED: Stiffness performance of polyethylene terephthalate modified asphalt mixtures estimation using support vector machine-firefly algorithm
نویسندگان
چکیده
منابع مشابه
MODELING OF FLOW NUMBER OF ASPHALT MIXTURES USING A MULTI–KERNEL BASED SUPPORT VECTOR MACHINE APPROACH
Flow number of asphalt–aggregate mixtures as an explanatory factor has been proposed in order to assess the rutting potential of asphalt mixtures. This study proposes a multiple–kernel based support vector machine (MK–SVM) approach for modeling of flow number of asphalt mixtures. The MK–SVM approach consists of weighted least squares–support vector machine (WLS–SVM) integrating two kernel funct...
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Plastics have prominent utilization worldwide. Polyethylene Terephthalate (PET) is one of the major types of plastics that can be found in the Municipal Solid Waste (MSW) [1]. MSW contains high proportion of thermoplastic polymers which has been increasing in value. PET is a semi-crystalline thermoplastic polymer, and is considered as polyester material [2]. Large amount of waste PET is being p...
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Prediction of daily evaporation is a valuable and determinant tool in sustainable agriculture and hydrological issues, especially in the design and management of water resources systems. Therefore, in this study, the ability of artificial intelligence models of multi-layer perceptron (MLP), support vector regression (SVR), and the hybrid model of support vector regression-firefly optimization a...
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The setting of parameters in the support vector machines (SVMs) is very important with regard to its accuracy and efficiency. In this paper, we employ the firefly algorithm to train all parameters of the SVM simultaneously, including the penalty parameter, smoothness parameter, and Lagrangian multiplier. The proposed method is called the firefly-based SVM (firefly-SVM). This tool is not conside...
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To prospect mineral deposits at regional scale, recognition and classification of hydrothermal alteration zones using remote sensing data is a popular strategy. Due to the large number of spectral bands, classification of the hyperspectral data may be negatively affected by the Hughes phenomenon. A practical way to handle the Hughes problem is preparing a lot of training samples until the size ...
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ژورنال
عنوان ژورنال: Measurement
سال: 2018
ISSN: 0263-2241
DOI: 10.1016/j.measurement.2018.03.048