PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Spatio-Temporal Road Condition Forecasting With Markov Chains and Artificial Neural Networks
Konsta Sirvio and Jaakko Hollmen
Third International Workshop in Hybrid Artificial Intelligent Systems (HAIS'08) Volume 5271, pp. 204-211, 2008.

Abstract

Preservation of the road assets value in an efficient manner is an important aim for developed road administrations. The task requires accurate road maintenance that is planned in advance. Forecasting road condition in the future is a prerequisite for optimisation of maintenance treatments. In this study two hybrid methods are introduced for forecasting road roughness and rutting. Markovian models outperform artificial neural network models and roughness can be forecast more accurately than rutting.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:4206
Deposited By:Jaakko Hollmen
Deposited On:21 November 2008