원문정보
초록
영어
Using data mining technology to analyze the huge amounts of meteorological data plays an important role in improving the accuracy of weather forecasts. After analyzed the features of meteorological data, a distributed meteorological data mining models using the pattern structure in formal concept analysis is proposed in this paper. Since there exists large numerical, boolean, and geographic concepts in meteorological data, using classic methods of formal concept analysis needs to build single-valued formal context. This paper adopts concept lattice pattern structure to avoid such conversions and the results of rules mining have higher readability and efficiency. This pattern structure of concept lattice is extended to the distributed model to improve data processing capability.
목차
1. Introduction
2. Basic Definition of Pattern Structure
3. Similar Computing in Meteorological Data
3.1. Numerical Interval
3.2. Geographical Regional Information
3.3. Boolean Value
3.4 Mixed Type Vector
4. The Construction of the Pattern of Concept Lattice
4.1 The Conversions of Pattern Structure
4.2 The Construction of the Pattern of Concept Lattice
5. Experimental Results and Analysis
6. Conclusion
Acknowledgements
References