Firstly, regional economic classification was made by clustering algorithms, which could be referenced by Support Vector Machine classification. Then Support Vector Machine classification was made to classificatory regional economic resources niche. Furthermore, more detailed classification was made under different economic resources niche indicators, which solve the problem of inadequate samples, making Categories strong operational and practical significance. Thus, more reasonable classification could be made by support vector machine model through the establishment of relatively small samples.

Date Published: 8 July 2011
PDF: 4 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80093I (8 July 2011);

Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)