首页|Researchers at Guangzhou University Release New Data on Machine Learning [Predicting the International Roughness Index of Jpcp and Crcp Rigid Pavement: a Random Forest (Rf) Model Hybridized With Modified Beetle Antennae Search (Mbas) for Higher ...]
Researchers at Guangzhou University Release New Data on Machine Learning [Predicting the International Roughness Index of Jpcp and Crcp Rigid Pavement: a Random Forest (Rf) Model Hybridized With Modified Beetle Antennae Search (Mbas) for Higher ...]
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Current study results on Machine Learning have been published. According to news reporting originating from Guangzhou, People's Republic of China, by NewsRx correspondents, research stated, "To improve the prediction accuracy of the International Roughness Index (IRI) of Jointed Plain Concrete Pavements (JPCP) and Continuously Reinforced Concrete Pavements (CRCP), a machine learning approach is developed in this study for the modelling, combining an improved Beetle Antennae Search (MBAS) algorithm and Random Forest (RF) model. The 10-fold cross-validation was applied to verify the reliability and accuracy of the model proposed in this study." Financial supporters for this research include Fundamental Research Funds for the Central Universities, Natural Science Foundation of Hunan Province, Hunan Provincial Transportation Technology Project. Our news editors obtained a quote from the research from Guangzhou University, "The importance scores of all input variables on the IRI of JPCP and CRCP were analysed as well. The results by the comparative analysis showed the prediction accuracy of the IRI of the newly developed MBAS and RF hybrid machine learning model (RF-MBAS) in this study is higher, indicated by the RMSE and R values of 0.2732 and 0.9476 for the JPCP as well as the RMSE and R values of 0.1863 and 0.9182 for the CRCP. The accuracy of this obtained result far exceeds that of the IRI prediction model used in the traditional Mechanistic-Empirical Pavement Design Guide (MEPDG), indicating the great potential of this developed model."
GuangzhouPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningGuangzhou University
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