1. Chen B, Pellicer S, Tai PC et al (2007) Super granular shrink-SVM feature elimination (Super GS-SVM-FE) model for protein sequence motif information extraction. Proceedings of the 7th IEEE international conference, pp 379–386.
2. Chen B, Pellicer S, Tai PC, Harrison R, Pan Y (2008) Efficient super granular SVM feature elimination (Super GSVM-FE) model for protein sequence motif information extraction[J]. Int J Funct Inform Pers Med 1: 8–25
3. Cheng W, Shi Y, Zhang YP (2007) Three primary mothods of granular computing. Comput Technol Dev 17(3): 91–94
4. Cheng W, Zhang YP, Zhao SH (2009) Research of yield prediction model based on support vector machine within the framework of quotient space theory. J Chin Agric Univ 14(5): 135–139
5. Cristianini N, Taylor JS (2004) An introduction to support vector machines and other kernel-based learning methods. Translated by LI Guo-zheng, WANG Meng. Publishing House of Electronics Industry, Beijing