Space Data Mining Research Based On Rough Set Theory

Rough sets theory is a new mathematic approach to uncertain and vague data analysis. Nowadays, it is, no doubt that one of the most challenging areas of modern computer applications and a new very important and rapidly growing area of research and applications. The applications of rough sets for knowledge discovery, data redution decision support, pattern recognition and others have proved to be a very effective new mathematic approach. The theory found many interesting real-life application in others. The uncertainty is a key issue for Remote Sensing theory and application, especially in classification. Evaluating and processing the uncertainty of the Remote Sensing information is an important task for RS application. As a result of that, the theme of "Rough Sets approach to Remote Sensing Image Processing and Classification " is selected as the main research topic of this dissertation. The detailed research work and suggestions can be sum up as the following:Using decision tree method of remote sensing images to practice the classification, discuss the similarities and differences in this two classification. Video image classification based on remote sensing knowledge and the use of geographic information systems knowledge feature selection and knowledge about Jane, in three rough set theory, the general rough set theory algorithm, heuristic algorithm and the rough set theory attribute reduction algorithm dynamic contrast study Uncertain information about the knowledge reduction algorithm. Remote sensing image classification rule based on the rules of knowledge extraction algorithm, using heuristic algorithm and dynamic calculation method regulatory rules extraction, and the actual data from experimental rules. Algorithm will be integrated image classification, the classification of rough set theory design and implementation, by the combination of three methods repeatedly together, the knowledge to achieve the best combination of classification methods, and the actual experimental data analysis, give the model and the classified. Rough set classification will be used in the same area over time as remote sensing, remote sensing image analysis to prove that the accuracy of the classification results, and can be understood by people in the form of expression, based on the pixel scale of the rough uncertainty after the document image classification Evaluation of the accuracy of that rough set theory of the validity of uncertain systems.Remote sensing data in the process of dealing with issues directly related to the uncertainty of dealing with the effects of good or bad, good handling mechanism help enhance capacity and improve the efficiency of processing algorithm. In remote sensing classification process, a lot of rough set theory of the effective application of places, such as reducing the high-dimensional data attributes and the ability and knowledge integration capabilities. In view of the current version of the more general use of the land use classification for the research direction, and there are many research studies and the limitations of the degree superficial. Hoped that invest more resources on research to find better and more intelligent automatic land use classification method, and rational development and utilization of land.