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Pavement Condition Index Prediction Using Fractional Order GM (1,1) Model
Author(s) -
Cai Lulu,
Wu Fei,
Lei Dongge
Publication year - 2021
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.23407
Subject(s) - gray (unit) , asphalt pavement , asphalt , pavement management , computer science , algorithm , data mining , engineering , mathematical optimization , civil engineering , mathematics , medicine , cartography , geography , radiology
Asphalt pavement performance prediction is an important issue for pavement management system. However, it is a difficult problem because asphalt pavement performance are affected by many factors. In this paper, a new method based on fractional gray model is proposed to predict the asphalt pavement performance with a limited data. The proposed method adopts fractional accumulating generating operation (FAGO) to replace traditional accumulating generating operation (AGO), which can be regarded as a weighted AGO emphasizing different contribution of data point for future prediction. An efficient differential evolution algorithm is adopted to select the best order of FAGO. Experimental results show that the proposed method can achieve higher prediction accuracy than conventional gray prediction model. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.