A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
This paper attempts to study the behavior of asphalt pavements using the fuzzy logic technique. The aim is to be able to determine the pavement condition after a certain time period, given the pavement construction materials, the age and the traffic to which the pavement is/will be exposed. The Long-Term Pavement Performance (LTPP) database is made use of in this paper. The data extracted from this database is used in the designing and testing of the Fuzzy Inference System. The membership functions of all the input parameters are built in accordance with these database records. The rules defining the behavior of the fuzzy inference system are written by taking into account the data available as well as by using logical reasoning. The end result is a system wherein if you enter the pavement data like construction materials, traffic and other pertinent data It can predict the rut depth after the required number of years. The resulting system can predict possible rut depths up to 15 years after construction.
This paper attempts to study the behavior of asphalt pavements using the fuzzy logic technique. The aim is to be able to determine the pavement condition after a certain time period, given the pavement construction materials, the age and the traffic to which the pavement is/will be exposed. The Long-Term Pavement Performance (LTPP) database is made use of in this paper. The data extracted from this database is used in the designing and testing of the Fuzzy Inference System. The membership functions of all the input parameters are built in accordance with these database records. The rules defining the behavior of the fuzzy inference system are written by taking into account the data available as well as by using logical reasoning. The end result is a system wherein if you enter the pavement data like construction materials, traffic and other pertinent data It can predict the rut depth after the required number of years. The resulting system can predict possible rut depths up to 15 years after construction.
Applying neuro-fuzzy techniques for intelligent highway pavement performance prediction model
2000
3 Seiten, 3 Quellen
Conference paper
English
Prediction of Pavement Performance through Neuro-Fuzzy Reasoning
| Online Contents | 2010
Neuro-Performance Modeling Applying Annual Pavement Data
| British Library Online Contents | 1997
Energy Evaluation of Highway Construction Using Neuro-Fuzzy Techniques
| Tema Archive | 2012