[1. Zadeh, L. A. Fuzzy Sets and Information Granulation. Advances in Fuzzy Set Theory and Applications. Amsterdam, North-Holland Publishing, 1979.]Search in Google Scholar
[2. Hobbs, J. R. Granularity. – In: Proc. of 9th International Joint Conference on Artificial Intelligence, Los Angeles, CA, 1985.]Search in Google Scholar
[3. Zadeh, L. A. Fuzzy Logic = Computing with Words. – IEEE Trans on Fuzzy Systems, Vol. 4, 1996, pp. 103-111.10.1109/91.493904]Search in Google Scholar
[4. Pawlak, Z. Rough Sets. 1982.10.1007/BF01001956]Search in Google Scholar
[5. Pawlak, Z. Rough Sets-Theoretical Aspects of Reasoning about Data. 1991.10.1007/978-94-011-3534-4]Search in Google Scholar
[6. Liu, R., X. Huang. The Granular Theorem of Quotient Space in Image Segmentation. – Chinese Journal of Computers, Vol. 28, 2005, No 10, pp. 1680-1685.]Search in Google Scholar
[7. Wang, G. Extension of Rough Set under Incomplete Information Systems. – Journal of Computer Research and Development, 2002, No 10, pp. 11-15.]Search in Google Scholar
[8. San, Y., Y. Ye. Rough Sets Theory and It’s Application in the Intelligent Systems. – CAAI Transactions on Intelligent Systems, Vol. 2, 2007, No 4, pp. 40-47.]Search in Google Scholar
[9. Zhang, L., B. Zhang. A Quotient Space Approximation Model of Multi Resolution Signal Analysis. – J. Computer Sci&Technol., Vol. 20, 2005, No 1, pp. 90-94.10.1007/s11390-005-0010-8]Search in Google Scholar
[10. Zhang, L., B. Zhang. Theory of Fuzzy Quotient Space (Methods of Fuzzy Granular Computing). – Journal of Software, Vol. 14, 2003, No 4, pp. 770-776.]Search in Google Scholar
[11. Yao, Y., C. Liau, N. Zhong. Granular Computing Based on Rough Sets, Quotient Space Theory, and Belief Functions. – In: Lecture Notes in Computer Science, 2003, pp. 152-159.10.1007/978-3-540-39592-8_21]Search in Google Scholar
[12. Zheng, Z. Tolerance Granular Space and It’s Applications. Beijing, Graduate School of the Chinese Academy of Science, 2006.]Search in Google Scholar
[13. Wang, G., Q. Zhang, J. Hu. An Overview of Granular Computing. – CAAI Transactions on Intelligent Systems, 2007, No 6, pp. 8-26.]Search in Google Scholar
[14. Zhang, Q., G. Wang, X. Yu. Approximation Sets of Rough Sets. – Journal of Software, 2012, No 7, pp. 1745-1759.10.3724/SP.J.1001.2012.04226]Search in Google Scholar
[15. Zhang, Q., G. Wang, X. Liu. Rule Acquisition Algorithm Based on Maximal Granule. – PR& AI, 2012, No 3, pp. 388-396.]Search in Google Scholar
[16. Li, L., K. Luo, B.-X. Zhuo. Rough Clustering Algorithm Based on Granular Computing. – Application Research of Computers, 2013, No 10, pp. 2916-2919.]Search in Google Scholar
[17. Li, H., S. Yang, H. Liu. Study of Qualitative Data Cluster Model Based on Granular Computing. – AASRI Procedia, 2013, pp. 329-333.10.1016/j.aasri.2013.10.048]Search in Google Scholar
[18. Yao, Y. Y., N. Zhong. Potential Applications of Granular Computing in Knowledge Discovery and Data Mining, 1999.]Search in Google Scholar
[19. Lin, T. Y. Encyclopedia of Complexity and Systems Science. New York, Springer, 2009.]Search in Google Scholar
[20. Leung, H., N. E. Faouzi, A. Kurian. Intelligent Transportation System (ITS). – Information Fusion, Vol. 12, 2011, No 1, pp. 2-3.10.1016/j.inffus.2010.06.003]Search in Google Scholar
[21. Gao, H., F. Liu. Combination Prediction Model of Traffic Flow Based on Rough Set Theory. – International Conference on Information Technology and Computer Science, 2009, pp. 425-428.10.1109/ITCS.2009.225]Search in Google Scholar
[22. He, F.-G., R. Liu, Y. Zhang, L. Zhang. BGrR: Large-Scale Network Routing Speedup Techniques Based on Granular Computing. – Computer Science, 2014, No 11, pp. 265-268, p. 281.]Search in Google Scholar
[23. Xiangen, B., Z. Hao, Z. Xiaodong et al. Support Vector Machine Regression Model with Rough Set-Based Feature Selection for Forecasting of Vessel Traffic Flow. – Computer Engineering& Applications, 2014.]Search in Google Scholar
[24. Ming-Jun, Q., S. Jian-Ye. Train Operation Adjustment Based on Rough Set Theory. – Journal of Transportation Systems Engineering & Information Technology, 2008.]Search in Google Scholar
[25. Jiang, G., L. H. Gang, X. D. Zhang et al. Malfunction Identifying and Modifying of Dynamic Traffic Data. – Journal of Traffic & Transportation Engineering, Vol. 4, 2004, No 1, pp. 121-125.]Search in Google Scholar
[26. Jiang Shun-Liang, Huang Xiao-Hui, Yang Li, Xu Shao-Ping. Research on Cellular Automata of Traffic Flow Based on Granular Computing. – Journal of Guangxi University. Nar. Sci. Ed., 2009, No 5, pp. 672-676.]Search in Google Scholar
[27. Zadeh, L. A. Fuzzy Sets. – Information and Control, Vol. 8, 1965, No 1, pp. 338-353. doi: 10.1016/S0019-9958(65)90241-X.10.1016/S0019-9958(65)90241-X]Search in Google Scholar
[28. Pawlak, Z. Rough Sets. – International Journal of Computer and Information Science, Vol. 11, 1982, No 5, pp. 341-356. doi: 10.1007/BF01001956.10.1007/BF01001956]Search in Google Scholar
[29. Zhang, L., B. Zhang. The Theory and Applications of Problem Solving-Quotient Space Based Granular Computing. 2nd Ed. Beijing, Tsinghua University Press, 2007 (in Chinese).]Search in Google Scholar
[30. Yao, Y. Y. Generalized Rough Set Models. L. Polkowski, A. Skowron, Eds. Rough Sets in Knowledge Discovery, Heidelberg, Physica-Verlag, 1998, pp. 286-318.]Search in Google Scholar