메뉴 건너뛰기




Volumn 9, Issue 1, 2009, Pages 1-12

Dimensionality reduction based on rough set theory: A review

Author keywords

Knowledge and classification; Metaheuristic; Neural network; Reduct; Rough set

Indexed keywords

ASSOCIATIVE PROCESSING; DATA MINING; DECISION SUPPORT SYSTEMS; DECISION THEORY; FUZZY SETS; INFORMATION MANAGEMENT; KNOWLEDGE BASED SYSTEMS; NETWORK PROTOCOLS; NEURAL NETWORKS; SENSOR NETWORKS; SET THEORY;

EID: 53749107899     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2008.05.006     Document Type: Review
Times cited : (352)

References (125)
  • 1
    • 53749104652 scopus 로고    scopus 로고
    • S.S.R. Abidi, K.M. Hoe, A. Goh, Analyzing Data Clusters: A Rough Set Approach To Extract Cluster-Defining Symbolic Rules, LNCS 2189, in: Proceedings of the IDA, 2001.
    • S.S.R. Abidi, K.M. Hoe, A. Goh, Analyzing Data Clusters: A Rough Set Approach To Extract Cluster-Defining Symbolic Rules, LNCS 2189, in: Proceedings of the IDA, 2001.
  • 5
    • 18344406127 scopus 로고    scopus 로고
    • Applying knowledge discovery to predict water-supply consumption
    • An A., Chan C., Shan N., Cercone N., and Ziarko W. Applying knowledge discovery to predict water-supply consumption. Expert IEEE 12 4 (1997) 72-78
    • (1997) Expert IEEE , vol.12 , Issue.4 , pp. 72-78
    • An, A.1    Chan, C.2    Shan, N.3    Cercone, N.4    Ziarko, W.5
  • 9
    • 0035502119 scopus 로고    scopus 로고
    • Reducts within the variable precision rough sets model: a further investigation
    • Beynon M. Reducts within the variable precision rough sets model: a further investigation. European Journal of Operational Research 134 (2001) 592-605
    • (2001) European Journal of Operational Research , vol.134 , pp. 592-605
    • Beynon, M.1
  • 11
    • 0032093405 scopus 로고    scopus 로고
    • A rough set approach to attribute generalization in data mining
    • Chan C.-C. A rough set approach to attribute generalization in data mining. Information Sciences 107 (1998) 169-176
    • (1998) Information Sciences , vol.107 , pp. 169-176
    • Chan, C.-C.1
  • 12
    • 35048884544 scopus 로고    scopus 로고
    • Learning rules from very large databases using rough multisets
    • Chan C.-C. Learning rules from very large databases using rough multisets. Transactions on Rough Sets 1 LNCS 3100 (2004) 55-77
    • (2004) Transactions on Rough Sets 1 LNCS 3100 , pp. 55-77
    • Chan, C.-C.1
  • 15
    • 53749083728 scopus 로고    scopus 로고
    • Sampling aspects of rough set theory
    • Curry B. Sampling aspects of rough set theory. Computational Management Science 1 (2004) 151-178
    • (2004) Computational Management Science , vol.1 , pp. 151-178
    • Curry, B.1
  • 16
    • 5044226706 scopus 로고    scopus 로고
    • Clustering web transactions using rough approximation
    • De S.K., and Radha Krishna P. Clustering web transactions using rough approximation. Fuzzy Sets and Systems 148 (2004) 131-138
    • (2004) Fuzzy Sets and Systems , vol.148 , pp. 131-138
    • De, S.K.1    Radha Krishna, P.2
  • 22
    • 0029492368 scopus 로고
    • A methodology for stock market analysis utilizing rough set theory
    • Golan R.H., and Ziarko W. A methodology for stock market analysis utilizing rough set theory. Proceedings of the IEEE/IAFE (1995) 32-40
    • (1995) Proceedings of the IEEE/IAFE , pp. 32-40
    • Golan, R.H.1    Ziarko, W.2
  • 23
    • 0032207398 scopus 로고    scopus 로고
    • Rough set extension of Tcl for data mining
    • Griffin G., and Chen Z. Rough set extension of Tcl for data mining. Knowledge-Based Systems 11 (1998) 249-253
    • (1998) Knowledge-Based Systems , vol.11 , pp. 249-253
    • Griffin, G.1    Chen, Z.2
  • 24
    • 4444353068 scopus 로고    scopus 로고
    • J.W. Grzymala-Busse, M. Hu, A comparison of several approaches to missing attribute values in data mining, in: W. Ziarko, Y. Yao (Eds.), RSCTS 2000, LNAI 2005, 2001, pp. 378-385.
    • J.W. Grzymala-Busse, M. Hu, A comparison of several approaches to missing attribute values in data mining, in: W. Ziarko, Y. Yao (Eds.), RSCTS 2000, LNAI 2005, 2001, pp. 378-385.
  • 29
    • 0032180332 scopus 로고    scopus 로고
    • Rough computational methods for information
    • Guan J.W., and Bell D.A. Rough computational methods for information. Artificial Intelligence 105 (1998) 77-103
    • (1998) Artificial Intelligence , vol.105 , pp. 77-103
    • Guan, J.W.1    Bell, D.A.2
  • 30
    • 84975475881 scopus 로고    scopus 로고
    • Hiearchical fault diagnosis for substation based on rough set
    • Haiying D., Yubo Z., and Junyi X. Hiearchical fault diagnosis for substation based on rough set. Proceedings of the Powercon 4 (2002) 2318-2321
    • (2002) Proceedings of the Powercon , vol.4 , pp. 2318-2321
    • Haiying, D.1    Yubo, Z.2    Junyi, X.3
  • 31
    • 4444310339 scopus 로고    scopus 로고
    • Rough set approach for attribute reduction and rule generation: a case of patients with suspected breast cancer
    • Hassanien A.-E. Rough set approach for attribute reduction and rule generation: a case of patients with suspected breast cancer. Journal of the American Society for Information Science and Technology 55 11 (2004) 954-962
    • (2004) Journal of the American Society for Information Science and Technology , vol.55 , Issue.11 , pp. 954-962
    • Hassanien, A.-E.1
  • 32
    • 53749091434 scopus 로고    scopus 로고
    • Enhanced rough sets rule reduction algorithm for classification digital mammography, intelligent system journal
    • Hassanien A.-E., and Ali J.M.H. Enhanced rough sets rule reduction algorithm for classification digital mammography, intelligent system journal. Freund & Pettman 13 2 (2004)
    • (2004) Freund & Pettman , vol.13 , Issue.2
    • Hassanien, A.-E.1    Ali, J.M.H.2
  • 35
    • 0020118274 scopus 로고
    • Neural networks and physical systems with emergent collective computational abilities
    • Hopfield J. Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences U S A (1982) 2554-2558
    • (1982) Proceedings of the National Academy of Sciences U S A , pp. 2554-2558
    • Hopfield, J.1
  • 36
    • 53749085382 scopus 로고    scopus 로고
    • K. Hu, Y. Lu, C. Shi, Sampling for Approximate Reduct in Very Large Datasets, http://www.lakecloud.xiloo.com/pkaw2000, http://www.citeseer.ist.psu.edu/587308.html, 2000.
    • K. Hu, Y. Lu, C. Shi, Sampling for Approximate Reduct in Very Large Datasets, http://www.lakecloud.xiloo.com/pkaw2000, http://www.citeseer.ist.psu.edu/587308.html, 2000.
  • 37
    • 4544223395 scopus 로고    scopus 로고
    • Using rough sets theory and database operations to construct a good ensemble of classifiers for data mining applications
    • Hu X. Using rough sets theory and database operations to construct a good ensemble of classifiers for data mining applications. Proceedings of ICDM (2001) 233-240
    • (2001) Proceedings of ICDM , pp. 233-240
    • Hu, X.1
  • 38
    • 0035509609 scopus 로고    scopus 로고
    • Discovering maximal generalized decision rules through horizontal and vertical reduction
    • Hu X., and Cercone N. Discovering maximal generalized decision rules through horizontal and vertical reduction. Computational Intelligence 17 4 (2001)
    • (2001) Computational Intelligence , vol.17 , Issue.4
    • Hu, X.1    Cercone, N.2
  • 41
    • 84888273942 scopus 로고    scopus 로고
    • P. Jaganathan, K. Thangavel, A. Pethalakshmi, M. Karnan, Classification rule discovery with ant colony optimization and improved Quick Reduct algorithm, Lecture Notes in Engineers and Computer Scientists, Hong Kong, 2006, pp. 286-291.
    • P. Jaganathan, K. Thangavel, A. Pethalakshmi, M. Karnan, Classification rule discovery with ant colony optimization and improved Quick Reduct algorithm, Lecture Notes in Engineers and Computer Scientists, Hong Kong, 2006, pp. 286-291.
  • 42
    • 0033083823 scopus 로고    scopus 로고
    • An investigation into the application of neural networks, fuzzy logic, genetic algorithms and rough sets to automated knowledge acquisition for classification problems
    • Jagielska I., Matthews C., and Whitfort T. An investigation into the application of neural networks, fuzzy logic, genetic algorithms and rough sets to automated knowledge acquisition for classification problems. Neurocomputing 24 (1999) 37-54
    • (1999) Neurocomputing , vol.24 , pp. 37-54
    • Jagielska, I.1    Matthews, C.2    Whitfort, T.3
  • 45
    • 0348170835 scopus 로고    scopus 로고
    • Fuzzy-rough attribute reduction with application to web categorization
    • Jensen R., and Shen Q. Fuzzy-rough attribute reduction with application to web categorization. Fuzzy Sets and Systems 141 3 (2004) 469-485
    • (2004) Fuzzy Sets and Systems , vol.141 , Issue.3 , pp. 469-485
    • Jensen, R.1    Shen, Q.2
  • 46
    • 10944249572 scopus 로고    scopus 로고
    • Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches
    • Jensen R., and Shen Q. Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches. IEEE Transactions on Knowledge and Data Engineering 16 12 (2004)
    • (2004) IEEE Transactions on Knowledge and Data Engineering , vol.16 , Issue.12
    • Jensen, R.1    Shen, Q.2
  • 47
    • 9644262464 scopus 로고    scopus 로고
    • Fuzzy-rough data reduction with ant colony optimization
    • Jensen R., and Shen Q. Fuzzy-rough data reduction with ant colony optimization. Fuzzy Sets and Systems 149 (2005) 5-20
    • (2005) Fuzzy Sets and Systems , vol.149 , pp. 5-20
    • Jensen, R.1    Shen, Q.2
  • 52
    • 0027002164 scopus 로고
    • The feature selection problem: traditional methods and a new algorithm
    • MIT Press
    • Kira K., and Rendell L.A. The feature selection problem: traditional methods and a new algorithm. Proceedings of AAAI (1992), MIT Press 129-134
    • (1992) Proceedings of AAAI , pp. 129-134
    • Kira, K.1    Rendell, L.A.2
  • 53
    • 0033084127 scopus 로고    scopus 로고
    • Modelling prognostic power of cardiac tests using rough sets
    • Komorowski J., and Ohrn A. Modelling prognostic power of cardiac tests using rough sets. Artificial Intelligence in Medicine 15 (1999) 167-191
    • (1999) Artificial Intelligence in Medicine , vol.15 , pp. 167-191
    • Komorowski, J.1    Ohrn, A.2
  • 59
    • 34250876927 scopus 로고    scopus 로고
    • Data decomposition and decision rule joining for classification of data with missing values
    • Latkowski R., and Mikolajczyk M. Data decomposition and decision rule joining for classification of data with missing values. Transactions on Rough Sets 1, LNCS 3100 (2004) 299-320
    • (2004) Transactions on Rough Sets 1, LNCS 3100 , pp. 299-320
    • Latkowski, R.1    Mikolajczyk, M.2
  • 60
    • 16244396746 scopus 로고    scopus 로고
    • Knowledge acquisition in incomplete information systems: a rough set approach
    • Leung Y., Wu W.Z., and Zhang W.-X. Knowledge acquisition in incomplete information systems: a rough set approach. European Journal of Operational Research 168 (2006) 164-180
    • (2006) European Journal of Operational Research , vol.168 , pp. 164-180
    • Leung, Y.1    Wu, W.Z.2    Zhang, W.-X.3
  • 61
    • 53749094706 scopus 로고    scopus 로고
    • J. Li, N. Cercrone, Empirical Analysis on the Geriatric Care Data Set Using Rough Sets Theory, Tech. Report, CS-2005-05, 2005.
    • J. Li, N. Cercrone, Empirical Analysis on the Geriatric Care Data Set Using Rough Sets Theory, Tech. Report, CS-2005-05, 2005.
  • 63
    • 2042476687 scopus 로고    scopus 로고
    • Mining classification rules using rough sets and neural networks
    • Li R., and Wang Z.-O. Mining classification rules using rough sets and neural networks. European Journal of Operational Research 157 (2004) 439-448
    • (2004) European Journal of Operational Research , vol.157 , pp. 439-448
    • Li, R.1    Wang, Z.-O.2
  • 65
    • 0034846943 scopus 로고    scopus 로고
    • The integrated of rough sets theory, fuzzy logic and genetic algorithms for multisensor fusion
    • Li Y.-R., and Jiang J.-P. The integrated of rough sets theory, fuzzy logic and genetic algorithms for multisensor fusion. Proceedings of the American Control Conference (2001)
    • (2001) Proceedings of the American Control Conference
    • Li, Y.-R.1    Jiang, J.-P.2
  • 70
    • 0036027422 scopus 로고    scopus 로고
    • Rule extraction from expert heuristics: a comparative study of rough sets with neural networks and ID3
    • Mak B., and Munakata T. Rule extraction from expert heuristics: a comparative study of rough sets with neural networks and ID3. European Journal of Operational Research 136 (2002) 212-229
    • (2002) European Journal of Operational Research , vol.136 , pp. 212-229
    • Mak, B.1    Munakata, T.2
  • 72
    • 0034492516 scopus 로고    scopus 로고
    • Evolutionary modular design of rough knowledge-based network using fuzzy attributes
    • Mitra S., Mitra P., and Pal S.K. Evolutionary modular design of rough knowledge-based network using fuzzy attributes. Neurocomputing 36 (2001) 45-66
    • (2001) Neurocomputing , vol.36 , pp. 45-66
    • Mitra, S.1    Mitra, P.2    Pal, S.K.3
  • 74
    • 53749084120 scopus 로고    scopus 로고
    • Rough set data representation using binary decision diagrams, RACSAM
    • Muir A., Duntsch I., and Gediga G. Rough set data representation using binary decision diagrams, RACSAM. Rev. R. Acad. Cien. Serie A. Mat 98 1 (2004) 197-211
    • (2004) Rev. R. Acad. Cien. Serie A. Mat , vol.98 , Issue.1 , pp. 197-211
    • Muir, A.1    Duntsch, I.2    Gediga, G.3
  • 75
    • 0033345951 scopus 로고    scopus 로고
    • Rule extraction based on rough set theory and its application to medical data analysis
    • Nakayama H., Hattori Y., and Ishii R. Rule extraction based on rough set theory and its application to medical data analysis. Proceedings of IEEESMC'99 5 (1999) 924-929
    • (1999) Proceedings of IEEESMC'99 , vol.5 , pp. 924-929
    • Nakayama, H.1    Hattori, Y.2    Ishii, R.3
  • 84
    • 53749084268 scopus 로고    scopus 로고
    • RSES: Rough Set Exploration System, http://logic.mimuw.edu.pl/∼rses/.
    • RSES: Rough Set Exploration System, http://logic.mimuw.edu.pl/∼rses/.
  • 85
    • 0029721663 scopus 로고    scopus 로고
    • Rough set-based data analysis in goal-oriented software measurement
    • Ruhe G. Rough set-based data analysis in goal-oriented software measurement. Proceedings of METRICS (1996) 10-19
    • (1996) Proceedings of METRICS , pp. 10-19
    • Ruhe, G.1
  • 87
    • 0034207737 scopus 로고    scopus 로고
    • A modular approach to generating fuzzy rules with reduced attributes for the monitoring of complex systems
    • Shen Q., and Chouchoulas A. A modular approach to generating fuzzy rules with reduced attributes for the monitoring of complex systems. Engineering Applications of Artificial Intelligence 13 3 (2002) 263-278
    • (2002) Engineering Applications of Artificial Intelligence , vol.13 , Issue.3 , pp. 263-278
    • Shen, Q.1    Chouchoulas, A.2
  • 88
    • 0036833247 scopus 로고    scopus 로고
    • A rough-fuzzy approach for generating classification rules
    • Shen Q., and Chouchoulas A. A rough-fuzzy approach for generating classification rules. Pattern Recognition 35 (2002) 2425-2438
    • (2002) Pattern Recognition , vol.35 , pp. 2425-2438
    • Shen, Q.1    Chouchoulas, A.2
  • 89
    • 2442528339 scopus 로고    scopus 로고
    • Selecting informative features with fuzzy-rough sets and its application for complex systems monitoring
    • Shen Q., and Jensen R. Selecting informative features with fuzzy-rough sets and its application for complex systems monitoring. Pattern Recognition 37 (2004) 1351-1363
    • (2004) Pattern Recognition , vol.37 , pp. 1351-1363
    • Shen, Q.1    Jensen, R.2
  • 90
    • 0024886040 scopus 로고
    • Rough classification in incomplete information systems
    • Slowinski R., and Stefanowski J. Rough classification in incomplete information systems. Mathematical Computer Modelling 12 10/11 (1989) 1347-1357
    • (1989) Mathematical Computer Modelling , vol.12 , Issue.10-11 , pp. 1347-1357
    • Slowinski, R.1    Stefanowski, J.2
  • 93
    • 0037332841 scopus 로고    scopus 로고
    • Rough set methods in feature selection and recognition
    • Swiniarski R.W., and Skowron A. Rough set methods in feature selection and recognition. Pattern Recognition Letters 24 (2003) 833-849
    • (2003) Pattern Recognition Letters , vol.24 , pp. 833-849
    • Swiniarski, R.W.1    Skowron, A.2
  • 94
    • 9944250506 scopus 로고    scopus 로고
    • Rule-based life cycle impact assessment using modified rough set induction methodology
    • Tan R.R. Rule-based life cycle impact assessment using modified rough set induction methodology. Environmental Modelling and Software 20 (2005) 509-513
    • (2005) Environmental Modelling and Software , vol.20 , pp. 509-513
    • Tan, R.R.1
  • 101
    • 53749104515 scopus 로고    scopus 로고
    • A novel reduct algorithm for dimensionality reduction with missing values based on rough set theory
    • Thangavel K., Pethalakshmi A., and Jaganathan P. A novel reduct algorithm for dimensionality reduction with missing values based on rough set theory. International Journal on Soft Computing 1 2 (2006) 111-117
    • (2006) International Journal on Soft Computing , vol.1 , Issue.2 , pp. 111-117
    • Thangavel, K.1    Pethalakshmi, A.2    Jaganathan, P.3
  • 102
    • 77952405945 scopus 로고    scopus 로고
    • K. Thangavel, M. Karnan, P. Jaganathan, R. Sivakumar, A. Pethalakshmi, Computer-Aided Diagnosis: Automatic detection of Microcalcifications in Mammographic Images using Soft Computing, Lecture Notes in Engineers and Computer Scientists, Hong Kong, 2006, pp. 280-285.
    • K. Thangavel, M. Karnan, P. Jaganathan, R. Sivakumar, A. Pethalakshmi, Computer-Aided Diagnosis: Automatic detection of Microcalcifications in Mammographic Images using Soft Computing, Lecture Notes in Engineers and Computer Scientists, Hong Kong, 2006, pp. 280-285.
  • 105
    • 53749087702 scopus 로고    scopus 로고
    • The ROSETTA homepage (http://www.idi.ntnu.no/∼aleks/rosetta/), Norwegian University of Science and Technology, Department of Computer and Information Science.
    • The ROSETTA homepage (http://www.idi.ntnu.no/∼aleks/rosetta/), Norwegian University of Science and Technology, Department of Computer and Information Science.
  • 106
    • 53749102202 scopus 로고    scopus 로고
    • Entropy-based fuzzy rough classification approach for extracting classification rules
    • Tsai Y.-C., Cheng C.-H., and Chang J.-R. Entropy-based fuzzy rough classification approach for extracting classification rules. Expert Systems with Applications (2005) 1-8
    • (2005) Expert Systems with Applications , pp. 1-8
    • Tsai, Y.-C.1    Cheng, C.-H.2    Chang, J.-R.3
  • 107
    • 23144447432 scopus 로고    scopus 로고
    • Feature-based rule induction in machining operation using rough set theory for quality assurance
    • Elsevier Publishers
    • (Bill)Tseng T.-L., Kwon Y., and Ertekin Y.M. Feature-based rule induction in machining operation using rough set theory for quality assurance. Robotics and Computer-Integrated Manufacturing (2005), Elsevier Publishers
    • (2005) Robotics and Computer-Integrated Manufacturing
    • (Bill)Tseng, T.-L.1    Kwon, Y.2    Ertekin, Y.M.3
  • 108
    • 2342616187 scopus 로고    scopus 로고
    • Mining diagnosis rules from clinical databases using rough sets and medical diagnostic model
    • Tsumaoto S. Mining diagnosis rules from clinical databases using rough sets and medical diagnostic model. Information Sciences 162 (2004) 65-80
    • (2004) Information Sciences , vol.162 , pp. 65-80
    • Tsumaoto, S.1
  • 110
    • 53749107183 scopus 로고    scopus 로고
    • A comparison of fuzzy C-means clustering and rough sets based classification in network data analysis
    • Interlaken, Switzerland
    • Vesa L., Timo L., Mikko L., and Hannu K. A comparison of fuzzy C-means clustering and rough sets based classification in network data analysis. Proceedings of WSEAS NNA-FSFS-EC. Interlaken, Switzerland (2002)
    • (2002) Proceedings of WSEAS NNA-FSFS-EC
    • Vesa, L.1    Timo, L.2    Mikko, L.3    Hannu, K.4
  • 112
    • 16244416222 scopus 로고    scopus 로고
    • On acquiring classification knowledge from noisy data based on rough set
    • Wang F.H. On acquiring classification knowledge from noisy data based on rough set. Expert Systems with Applications 29 (2005) 49-64
    • (2005) Expert Systems with Applications , vol.29 , pp. 49-64
    • Wang, F.H.1
  • 113
    • 22944457382 scopus 로고    scopus 로고
    • A hybrid method for relevance feedback in image retrieval using rough sets and neural networks
    • Wang Y., Ding M., Zhou C., and Zhang T. A hybrid method for relevance feedback in image retrieval using rough sets and neural networks. International Journal of Computational Cognition 3 1 (2005)
    • (2005) International Journal of Computational Cognition , vol.3 , Issue.1
    • Wang, Y.1    Ding, M.2    Zhou, C.3    Zhang, T.4
  • 117
    • 2342651489 scopus 로고    scopus 로고
    • Reducing inconsistent rules based on irregular decision table
    • Yidong L., Ling Z., and Lianchen L. Reducing inconsistent rules based on irregular decision table. Tsinghua Science and Technology 9 1 (2004) 45-50
    • (2004) Tsinghua Science and Technology , vol.9 , Issue.1 , pp. 45-50
    • Yidong, L.1    Ling, Z.2    Lianchen, L.3
  • 120
    • 21244485493 scopus 로고    scopus 로고
    • Development of a noise sources classification system based on new method for feature selection
    • Zeng X., and Zhan Y. Development of a noise sources classification system based on new method for feature selection. Applied Acoustics 66 (2005) 1196-1205
    • (2005) Applied Acoustics , vol.66 , pp. 1196-1205
    • Zeng, X.1    Zhan, Y.2
  • 121
    • 33746266322 scopus 로고    scopus 로고
    • J. Zhang, J. Wang, D. Li, H. He, J. Sun, A New Heuristic Reduct Algorithm Base on Rough Sets Theory, LNCS 2762, Springer-Verlag, 2003, pp. 247-253.
    • J. Zhang, J. Wang, D. Li, H. He, J. Sun, A New Heuristic Reduct Algorithm Base on Rough Sets Theory, LNCS 2762, Springer-Verlag, 2003, pp. 247-253.
  • 122
    • 4544306553 scopus 로고    scopus 로고
    • A rough sets based approach to feature selection, fuzzy information
    • Zhang M., and Yao J.T. A rough sets based approach to feature selection, fuzzy information. Processing NAFIPS'04 1 (2004) 434-439
    • (2004) Processing NAFIPS'04 , vol.1 , pp. 434-439
    • Zhang, M.1    Yao, J.T.2
  • 125
    • 0037621960 scopus 로고    scopus 로고
    • Reduction and axiomization of covering generalized rough sets
    • Zhu W., and Wang F.-Y. Reduction and axiomization of covering generalized rough sets. Information Sciences 152 (2003) 217-230
    • (2003) Information Sciences , vol.152 , pp. 217-230
    • Zhu, W.1    Wang, F.-Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.