Digital Library

of the European Council for Modelling and Simulation



Hydrometeorologic Social Network With CBR Prediction


Tomáń Kocyan, Jan Martinovič, Andrea Valičková, Boris Ńír,

Michaela Hořínková, Veronika Říhová

Published in:


(2010).ECMS 2010 Proceedings edited by A Bargiela S A Ali D Crowley E J H Kerckhoffs. European Council for Modeling and Simulation. doi:10.7148/2010 


ISBN: 978-0-9564944-1-2


24th European Conference on Modelling and Simulation,

Simulation Meets Global Challenges

Kuala Lumpur, June 1-4 2010


Citation format:

Kocyan, T., Martinovič, J., Valičková, A., Šír, B., Hořínková, M., & Říhová, V. (2010). Hydrometeorologic Social Network With CBR Prediction. ECMS 2010 Proceedings edited by A Bargiela S A Ali D Crowley E J H Kerckhoffs (pp. 233-241). European Council for Modeling and Simulation. doi:10.7148/2010-0233-0241



Human activities are contributing to more frequent natu- ral extremes and climate change, which also come from the atmosphere, water or the Earths crust. With the in- creasing development of infrastructure, the impacts of these changes and extremes leave more perceivable dam- age and increasing loss of lives and property. With the use of modern resources and technology we are able to minimize the impact of these extreme phenomena. There are in fact two main approaches - professional and non- professional - both meant from the aspect of data collec- tion and information processing itself. The advantages of social networks have been increasingly utilized dur- ing the natural disasters as a way of communicating im- portant information. This article describes the aim of our research - to create a hybrid system which would both enable the collection of data from the professional and non-professional public as well as communicate with other types of systems, to utilize and then process the data and use the data to predict new dangers. The prin- ciple is based on collecting data (knowledge, experience, etc.) from both main approaches to disaster management (professional and nonprofessional) and then applying this information to achieve new solutions. The practical ap- plication of a DIP system shows that it can be used for describing the risk of future natural disasters and enables us to deduce the threat imposed by them. Analyzing this data can help create new solutions in the fight to mini- mize the damage incurred by these disasters.

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