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Volume 2017 (2017), Article ID 3418145, 10 pages
Research Article

Development of ANN Model for Wind Speed Prediction as a Support for Early Warning System

1Department of Construction Management and Technology, Faculty of Civil Engineering, University of Rijeka, 51000 Rijeka, Croatia
2Department of Hydraulic Engineering and Geotechnical Engineering, Faculty of Civil Engineering, University of Rijeka, 51000 Rijeka, Croatia

Correspondence should be addressed to Ivana Sušanj

Received 28 September 2017; Accepted 28 November 2017; Published 20 December 2017

Academic Editor: Milos Knezevic

Copyright © 2017 Ivan Marović et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The impact of natural disasters increases every year with more casualties and damage to property and the environment. Therefore, it is important to prevent consequences by implementation of the early warning system (EWS) in order to announce the possibility of the harmful phenomena occurrence. In this paper, focus is placed on the implementation of the EWS on the micro location in order to announce possible harmful phenomena occurrence caused by wind. In order to predict such phenomena (wind speed), an artificial neural network (ANN) prediction model is developed. The model is developed on the basis of the input data obtained by local meteorological station on the University of Rijeka campus area in the Republic of Croatia. The prediction model is validated and evaluated by visual and common calculation approaches, after which it was found that it is possible to perform very good wind speed prediction for time steps , , and . The developed model is implemented in the EWS as a decision support for improvement of the existing “procedure plan in a case of the emergency caused by stormy wind or hurricane, snow and occurrence of the ice on the University of Rijeka campus.”