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Cited by 42 publications
(6 citation statements)
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“…We consider having PCI as the most complex variable into the target and the cheap and practical obtaining variable by the predictors, resulting from the automatic linear modeling. The result shows more than 77% accuracy and the IRI (Hossain et al, 2020) as an essential predictor with 55.8% contribution in the result, and an acceptable significance level of 0.000; as the layer1_transformed with 12.8% have acceptable importance among them while it shows speed does not have a considerable contribution in the prediction result. Then, we run another multi regression with more variables and result in which some variables have a high contribution.…”
Section: Multivariate Linear Regressionmentioning
confidence: 87%
“…We consider having PCI as the most complex variable into the target and the cheap and practical obtaining variable by the predictors, resulting from the automatic linear modeling. The result shows more than 77% accuracy and the IRI (Hossain et al, 2020) as an essential predictor with 55.8% contribution in the result, and an acceptable significance level of 0.000; as the layer1_transformed with 12.8% have acceptable importance among them while it shows speed does not have a considerable contribution in the prediction result. Then, we run another multi regression with more variables and result in which some variables have a high contribution.…”
Section: Multivariate Linear Regressionmentioning
confidence: 87%
“…In 2008, Ngwangwa et al used the displacement obtained from the simulation of a two-degrees-of-freedom model of a 1/4 car as the input of a backpropagation (BP) neural network to achieve the recognition of the road roughness grade [ 10 , 11 ]. Hossain et al focused on predicting the international roughness index (IRI) of rigid pavements using an artificial neural network (ANN) model that uses climate and traffic parameters as inputs [ 12 , 13 ]. Ziari et al analyzed the capability of the support-vector machine (SVM) method to predict the pavement’s future condition [ 14 ].…”
Section: Introductionmentioning
confidence: 99%
“…Hossain [9] divided the pavement data into four categories through climatic characteristics, established a neural network model to predict the four types of data, and tried different activation functions to test.…”
Section: Introductionmentioning
confidence: 99%