Introduction
Recently, there are a lot of researches concerned with natural disaster simulation by using data gathering useful information from sensors and climate management systems. However, most of simulations are based on high specs computers since the simulation is conducted with numerical and quantitative method[1][2][4][7]. By using huge data such as climate, temperature, and other physical status about degree of altitude, the simulation gives a rigorous result of analysis even though the situation and circumstance is complex like property of the atmosphere. Further, they are also developed for specialist but naive users and novices.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Agell, N., Aguado, C.J.: A hybrid qualitative-quantitative classification technique applied to aid marketing decisions. In: The proceedings of 11th International Workshop on Qualitative Reasoning (2001)
Bredeweg, B., Winkels, R.: Qualitative models in interactive learning environments. Interactive Learning Environments 5 (1998)
Chen, S.A., Wang, J., Yang, C.S.: Constructing internet futures exchange for teach-ing derivatives trading in financial markets. In: The proceedings of International Conference on Computers in Education, vol. 2, pp. 1392–1395 (2002)
Forbus, K.D.: Helping children become qualitative modelers. Journal of the Japanese Society for Artificial Intelligence 17(4) (2002)
Hata, S., Ohkawa, T., Komoda, N.: Backward simulation method in qualitative simulation. IEEJ Transactions on Electronics, Information and Systems, Institute of Electrical Engineers of Japan 115-C(11) (1995)
Kuipers, B.: Qualitative Reasoning. The MIT Press, Cambridge (1994)
Matsuo, T., Ito, T., Shintani, T.: A qualitative/quantitative methods-based e-learning support system in economic education. In: The 19th National Conference on Artificial Intelligence (AAAI 2004) (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Matsuo, T., Hatano, N. (2009). Multiple Factors Based Qualitative Simulation for Flood Analysis. In: Lee, R., Ishii, N. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Studies in Computational Intelligence, vol 209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01203-7_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-01203-7_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01202-0
Online ISBN: 978-3-642-01203-7
eBook Packages: EngineeringEngineering (R0)