A meteorological conceptual modeling approach based on spatial data mining and knowledge discovery

Authors:
Yang Yubin;Lin Hui;Guo Zhongyang;Jiang Jixi
Affiliations:
State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, P. R. China and Joint Laboratory for Geoinformation Science, The Chinese University of Hong Kong, Shatin, N.T., Hon ...;Joint Laboratory for Geoinformation Science, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong;Joint Laboratory for Geoinformation Science, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong;National Satellite Meteorological Center, China Meteorological Administration, Beijing, P. R. China
Venue:
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Year:
2005

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Abstract

Conceptual models play an important part in a variety of domains, especially in meteorological applications. This paper proposes a novel conceptual modeling approach based on a two-phase spatial data mining and knowledge discovery method, aiming to model the concepts of the evolvement trends of Mesoscale Convective Clouds (MCCs) over the Tibetan Plateau with derivation rules and environmental physical models. Experimental results show that the proposed conceptual model to much extent simplifies and improves the weather forecasting techniques on heavy rainfalls and floods in South China.