Artificial intelligence techniques represent an efficacious approach both to implement predictive models and to resolve optimization problems. They are, therefore, particularly appropriate for pavement maintenance management. In this paper, a procedure has been defined to make use of the available economic resources in the best way possible for resurfacing interventions on flexible pavements by using artificial neural networks and genetic algorithms. The neural networks, in particular, were utilized to define both a Sideway Force Coefficient prediction model and an accident prediction model. The optimization problem was resolved by means of an opportunely defined genetic algorithm using the results of the neural networks designed. The procedure was applied to the A18 motorway of the Eastern Sicily road network. The obtained results have highlighted that the procedure represents an efficient approach to obtain one of optimal solutions in a very big space of possible solutions in sufficiently short periods of time.

A Model Based on Artificial Neural Network and Genetic Algorithms for Pavement Maintenance Management

BOSURGI, Gaetano;
2005

Abstract

Artificial intelligence techniques represent an efficacious approach both to implement predictive models and to resolve optimization problems. They are, therefore, particularly appropriate for pavement maintenance management. In this paper, a procedure has been defined to make use of the available economic resources in the best way possible for resurfacing interventions on flexible pavements by using artificial neural networks and genetic algorithms. The neural networks, in particular, were utilized to define both a Sideway Force Coefficient prediction model and an accident prediction model. The optimization problem was resolved by means of an opportunely defined genetic algorithm using the results of the neural networks designed. The procedure was applied to the A18 motorway of the Eastern Sicily road network. The obtained results have highlighted that the procedure represents an efficient approach to obtain one of optimal solutions in a very big space of possible solutions in sufficiently short periods of time.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11570/1433805
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