The Predicted Model of International Roughness Index for Drainage Asphalt Pavement

  • Authors:

  • Chien-Ta Chen;Ching-Tsung Hung;Chien-Cheng Chou;Ziping Chiang;Jyh-Dong Lin

  • Affiliations:

  • Department of Civil Engineering, National Central University, Taoyuan County, Taiwan (R.O.C.) 32001;Department of Transportation Technology and Supply Chain, Kainan University, Taoyuan County, Taiwan (R.O.C.) 33857;Department of Civil Engineering, National Central University, Taoyuan County, Taiwan (R.O.C.) 32001;Department of Logistics Management, Leader University, Tainan City, Taiwan (R.O.C.) 709;Department of Civil Engineering, National Central University, Taoyuan County, Taiwan (R.O.C.) 32001

  • Venue:
  • ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

Roughness is a very important performance indicator in pavement maintenance management systems. The international rough index (IRI) of indicators was used as the core of roughness measuring of degree gradually in recent years domestically, but to predict a smooth degree of indicators the method is set up differently as there is a different prediction indicator because the theoretical foundation is different. This research bases its measurement data on the porous asphalt pavement of national highway number 3. We predicts the deterioration of IRI by different ways, including grey forecast, multiple regression, genetic programming. The result of this research found that there are better results in genetic programming method prediction than roughness index foundation method. The reason that it accords with the best prediction result is that heredity can carry on the change to plan in the parameter.