- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Annual Issues
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Journal of Applied Mathematics
Volume 2012 (2012), Article ID 857590, 14 pages
Parameterized Local Reduction of Decision Systems
Department of Mathematics and Physics, North China Electric Power University, Beijing 102206, China
Received 25 May 2012; Revised 17 September 2012; Accepted 3 October 2012
Academic Editor: Juan Manuel Peña
Copyright © 2012 Degang Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Z. Pawlak, “Rough sets,” International Journal of Computer and Information Sciences, vol. 11, no. 5, pp. 341–356, 1982.
- J. Bazan, “A comparison of dynamic and non-dynamic rough set methods for extracting laws from decision tables,” in Rough Sets in Knowledge Discovery, L. Polkowski and A. Skowron, Eds., pp. 321–365, Physica, Heidelberg, Germany, 1998.
- M. Beynon, “Reducts within the variable precision rough sets model: a further investigation,” European Journal of Operational Research, vol. 134, pp. 592–605, 2001.
- J. Grzymala-Busse and X. Zuo, “Classification strategies using certain and possible rules,” in Proceedings of the 1st International Conference on Rough Sets and Current Trends in Computing (RSCTC '98), vol. 1424 of LANI, pp. 37–44, Springer, 1998.
- M. Kryszkiewicz, “Comparative study of alternative type of knowledge reduction in inconsistent systems,” International Journal of Intelligent System, vol. 16, pp. 105–120, 2001.
- M. Kryszkiewicz, “Rough set approach to incomplete information systems,” Information Sciences, vol. 112, no. 1–4, pp. 39–49, 1998.
- Y. Leung, J.-M. Ma, W.-X. Zhang, and T.-J. Li, “Dependence-space-based attribute reductions in inconsistent decision information systems,” International Journal of Approximate Reasoning, vol. 49, no. 3, pp. 623–630, 2008.
- Y. Leung, W.-Z. Wu, and W.-X. Zhang, “Knowledge acquisition in incomplete information systems: a rough set approach,” European Journal of Operational Research, vol. 168, no. 1, pp. 164–180, 2005.
- J.-S. Mi, W.-Z. Wu, and W.-X. Zhang, “Approaches to knowledge reduction based on variable precision rough set model,” Information Sciences, vol. 159, no. 3-4, pp. 255–272, 2004.
- H. S. Nguyen and D. Slezak, “Approximation reducts and association rules correspondence and complexity results,” in Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing (RSFDGrC '99), N. Zhong, A. Skowron, and S. Oshuga, Eds., vol. 1711 of LNAI, pp. 137–145, Yamaguchi, Japan, 1999.
- Z. Pawlak and R. Sets, Theoretical Aspects of Reasoning About Data, Kluwer Academic Publishers, Boston, Mass, USA, 1991.
- A. Skowron and C. Rauszer, “The discernibility matrices and functions in information systems,” in Intelligent Decision Support-Handbook of Applications and Advances of the Rough Sets Theory, R. Slowinski, Ed., pp. 331–362, Kluwer Academic Publishers, 1992.
- D. Slezak, “Approximate reducts in decision tables,” in Proceedings of 6th International Conference Information Procesing and Management of Uncertainty in Knowledge-Based Systems (IPMU '96), vol. 3, pp. 1159–1164, Granada, Spain, 1996.
- D. Slezak, “Searching for dynamic reducts in inconsistent decision tables,” in Proceedings of 7th International Conference Information Procesing and Management of Uncertainty in Knowledge-Based Systems (IPMU '98), vol. 2, pp. 1362–1369, Paris, France, 1998.
- G. Y. Wang, “Algebra view and information view of rough sets theory,” in Data Mining and Knowledge Discovery: Theory, Tools, and Technology III, B. V. Dasarathy, Ed., vol. 4384 of Proceedings of SPIE, pp. 200–207, 2001.
- G. Y. Wang, H. Yu, and D. C. Yang, “Decision table reduction based on conditional information entropy,” Chinese Journal of Computers, vol. 25, no. 7, pp. 759–766, 2002.
- G. Y. Wang, “Rough reduction in algebra view and information view,” International Journal of Intelligent System, vol. 18, pp. 679–688, 2003.
- W.-Z. Wu, M. Zhang, H.-Z. Li, and J.-S. Mi, “Knowledge reduction in random information systems via Dempster-Shafer theory of evidence,” Information Sciences, vol. 174, no. 3-4, pp. 143–164, 2005.
- W.-X. Zhang, J.-S. Mi, and W.-Z. Wu, “Approaches to knowledge reductions in inconsistent systems,” International Journal of Intelligent Systems, vol. 18, pp. 989–1000, 2003.
- W.-X. Zhang and G.-F. Qiu, Uncertain Decision Making Based on Rough Sets, vol. 6 of Uncertainty Theory and Optimization Series, Tsinghua University Press, Beijing, China, 2005.
- W.-X. Zhang, W.-Z. Wu, J.-Y. Liang, and D.-Y. Li, Theory and Method of Rough Sets, Science Press, Beijing, China, 2001.
- W. Ziarko, “Variable precision rough set model,” Journal of Computer and System Sciences, vol. 46, no. 1, pp. 39–59, 1993.
- W. Ziarko, “Analysis of uncertain information in the framework of variable precision rough sets,” Foundations of Computing and Decision Sciences, vol. 18, pp. 381–396, 1993.
- J. Zhou, J. Y. Wang, and A. Luo, “Analysis of characteristics reducts in variable precision rough sets,” Application Research of Computers, vol. 24, no. 7, pp. 10–15, 2007.
- UCI Machine Learning Repository, http://archive.ics.uci.edu/ml/.
- D. Yu, Q. Hu, and W. Bao, “Combining rough set methodology and fuzzy clustering for knowledge discovery from quantitative data,” Proceeding of Chinese Society of Electrical Engineering, vol. 24, no. 6, pp. 205–210, 2004.