Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDPawan Lingras
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2020
[c85]Nikita Neveditsin, Ross MacDonald, Pawan Lingras, Trent Hillard:
Modeling User Feedback: Fuzzy sampling, Portability, and Degree of Annoyance. FUZZ-IEEE 2020: 1-7
2010 – 2019
- 2019
- [j41]Hong Yu, Yun Chen, Pawan Lingras, Guoyin Wang:
A three-way cluster ensemble approach for large-scale data. Int. J. Approx. Reason. 115: 32-49 (2019) - [c84]Ross MacDonald, Nikita Neveditsin, Pawan Lingras, Zheng Qin, Trent Hillard:
Sampling Using Fuzzy and Crisp Clustering to Improve Recall of Building Comfort Feedback. FUZZ-IEEE 2019: 1-6 - [c83]Ross MacDonald, Nikita Neveditsin, Pawan Lingras, Trent Hillard:
Effect of Maximizing Recall and Agglomeration of Feedback on Accuracy. IFSA/NAFIPS 2019: 351-361 - 2018
- [c82]Matt Triff, Ilya Pavlovski, Zhixing Liu, Lori-Anne Morgan, Pawan Lingras:
Fuzzy Clustering Ensemble for Prioritized Sampling Based on Average and Rough Patterns. IEA/AIE 2018: 661-669 - 2017
- [c81]Matt Triff, Glavin Wiechert, Pawan Lingras:
Nonlinear classification, linear clustering, evolutionary semi-supervised three-way decisions: A comparison. FUZZ-IEEE 2017: 1-6 - [c80]Matt Triff, Ilya Pavlovski, Zhixing Liu, Lori-Anne Morgan, Pawan Lingras:
Clustering Ensemble for Prioritized Sampling Based on Average and Rough Patterns. ISMIS 2017: 530-539 - 2016
- [j40]Pawan Lingras:
Book Review: Cognitive Computing: Theory and Applications. IEEE Intell. Informatics Bull. 17(1): 27 (2016) - [j39]Asma Ammar, Zied Elouedi
, Pawan Lingras:
Meta-clustering of possibilistically segmented retail datasets. Fuzzy Sets Syst. 286: 173-196 (2016) - [c79]Glavin Wiechert, Matt Triff, Zhixing Liu, Zhicheng Yin, Shuai Zhao, Ziyun Zhong, Runxing Zhaou, Pawan Lingras:
Identifying users and activities with cognitive signal processing from a wearable headband. ICCI*CC 2016: 129-136 - [c78]Glavin Wiechert, Matt Triff, Zhixing Liu, Zhicheng Yin, Shuai Zhao, Ziyun Zhong, Pawan Lingras:
Evolutionary semi-supervised rough categorization of brain signals from a wearable headband. CEC 2016: 3131-3138 - [c77]Pawan Lingras, Matt Triff:
Advances in Rough and Soft Clustering: Meta-Clustering, Dynamic Clustering, Data-Stream Clustering. IJCRS 2016: 3-22 - 2015
- [j38]Pawan Lingras, Sugata Sanyal:
Book Review: Big Data Analytics. IEEE Intell. Informatics Bull. 16(1): 28-29 (2015) - [j37]Pawan Lingras, Farhana Haider:
Partially ordered rough ensemble clustering for multigranular representations. Intell. Data Anal. 19(s1): S103-S116 (2015) - [j36]Asma Ammar, Zied Elouedi, Pawan Lingras:
Semantically Segmented Clustering Based on Possibilistic and Rough Set Theories. Int. J. Intell. Syst. 30(6): 676-706 (2015) - [j35]Pawan Lingras, Matt Triff:
Fuzzy and Crisp Recursive Profiling of Online Reviewers and Businesses. IEEE Trans. Fuzzy Syst. 23(4): 1242-1258 (2015) - [c76]Jason P. Rhinelander, Mathew Kallada, Pawan Lingras:
Visual Predictions of Traffic Conditions. Canadian Conference on AI 2015: 122-129 - [c75]Pawan Lingras, Farhana Haider:
Combining Rough Clustering Schemes as a Rough Ensemble. RSKT 2015: 383-394 - 2014
- [j34]Pawan Lingras, Min Chen, Duoqian Miao:
Qualitative and quantitative combinations of crisp and rough clustering schemes using dominance relations. Int. J. Approx. Reason. 55(1): 238-258 (2014) - [j33]Pawan Lingras, Ahmed Elagamy, Asma Ammar, Zied Elouedi:
Iterative meta-clustering through granular hierarchy of supermarket customers and products. Inf. Sci. 257: 14-31 (2014) - [c74]Asma Ammar, Zied Elouedi, Pawan Lingras:
Rough possibilistic meta-clustering of retail datasets. DSAA 2014: 177-183 - [c73]Asma Ammar, Zied Elouedi, Pawan Lingras:
Decremental Rough Possibilistic K-Modes. ICAIS 2014: 50-59 - [c72]Georg Peters, Pawan Lingras:
Analysis of User-Weighted π Rough k-Means. RSKT 2014: 547-556 - [c71]Asma Ammar, Zied Elouedi, Pawan Lingras:
Semantically Enhanced Clustering in Retail Using Possibilistic K-Modes. RSKT 2014: 753-764 - 2013
- [j32]Georg Peters, Fernando A. Crespo, Pawan Lingras, Richard Weber:
Soft clustering - Fuzzy and rough approaches and their extensions and derivatives. Int. J. Approx. Reason. 54(2): 307-322 (2013) - [c70]Saurabh Nagrecha, Pawan Lingras, Nitesh V. Chawla:
Comparison of Gene Co-expression Networks and Bayesian Networks. ACIIDS (1) 2013: 507-516 - [c69]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Exhaustive Search with Belief Discernibility Matrix and Function. Canadian Conference on AI 2013: 162-173 - [c68]Asma Ammar, Zied Elouedi, Pawan Lingras:
The K-Modes Method under Possibilistic Framework. Canadian Conference on AI 2013: 211-217 - [c67]Kishore Rathinavel, Pawan Lingras:
A granular recursive fuzzy meta-clustering algorithm for social networks. IFSA/NAFIPS 2013: 567-572 - [c66]Asma Ammar, Zied Elouedi, Pawan Lingras:
The k-modes method using possibility and rough set theories. IFSA/NAFIPS 2013: 1297-1302 - [c65]Asma Ammar, Zied Elouedi, Pawan Lingras:
Incremental Rough Possibilistic K-Modes. MIWAI 2013: 13-24 - [c64]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Belief Discernibility Matrix and Function for Incremental or Large Data. RSFDGrC 2013: 67-76 - [c63]Manish Joshi, Pawan Lingras:
Enhancing Rough Clustering with Outlier Detection Based on Evidential Clustering. RSFDGrC 2013: 127-137 - [c62]Asma Ammar, Zied Elouedi, Pawan Lingras:
Incremental Possibilistic K-Modes. RSFDGrC 2013: 293-303 - [c61]Matt Triff, Pawan Lingras:
Recursive Profiles of Businesses and Reviewers on Yelp.com. RSFDGrC 2013: 325-336 - [c60]Asma Ammar, Zied Elouedi, Pawan Lingras:
Decremental Possibilistic K-Modes. SCAI 2013: 15-24 - [p3]Pawan Lingras, Parag Bhalchandra, Cory J. Butz, S. Asharaf:
Rough Support Vectors: Classification, Regression, Clustering. Rough Sets and Intelligent Systems (1) 2013: 491-515 - [e9]Sheela Ramanna, Pawan Lingras, Chattrakul Sombattheera, Aneesh Krishna:
Multi-disciplinary Trends in Artificial Intelligence - 7th International Workshop, MIWAI 2013, Krabi, Thailand, December 9-11, 2013. Proceedings. Lecture Notes in Computer Science 8271, Springer 2013, ISBN 978-3-642-44948-2 [contents] - [e8]Pawan Lingras, Marcin Wolski, Chris Cornelis, Sushmita Mitra, Piotr Wasilewski:
Rough Sets and Knowledge Technology - 8th International Conference, RSKT 2013, Halifax, NS, Canada, October 11-14, 2013, Proceedings. Lecture Notes in Computer Science 8171, Springer 2013, ISBN 978-3-642-41298-1 [contents] - [i2]S. K. Michael Wong, Y. Y. Yao, Pawan Lingras:
Compatibility of Quantitative and Qualitative Representations of Belief. CoRR abs/1303.5758 (2013) - [i1]S. K. Michael Wong, Pawan Lingras:
Combination of Evidence Using the Principle of Minimum Information Gain. CoRR abs/1304.1135 (2013) - 2012
- [j31]Manish Joshi, Pawan Lingras, C. Raghavendra Rao:
Correlating Fuzzy and Rough Clustering. Fundam. Informaticae 115(2-3): 233-246 (2012) - [c59]Pawan Lingras, Parag Bhalchandra, Santosh Khamitkar, Satish Mekewad, Ravindra Rathod:
Propagation of knowledge from crisp and soft clustering through a granular hierarchy. HIS 2012: 6-11 - [c58]Asma Ammar, Zied Elouedi, Pawan Lingras:
K-Modes Clustering Using Possibilistic Membership. IPMU (3) 2012: 596-605 - [c57]Pawan Lingras, Kishore Rathinavel:
Recursive meta-clustering in a granular network. ISDA 2012: 770-775 - [c56]Asma Ammar, Zied Elouedi, Pawan Lingras:
RPKM: The Rough Possibilistic K-Modes. ISMIS 2012: 81-86 - [c55]Manish Joshi, Pawan Lingras:
Evidential Clustering or Rough Clustering: The Choice Is Yours. RSKT 2012: 123-128 - [c54]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Heuristic for Attribute Selection Using Belief Discernibility Matrix. RSKT 2012: 129-138 - 2011
- [j30]Cory J. Butz, Ken Konkel, Pawan Lingras:
Join tree propagation utilizing both arc reversal and variable elimination. Int. J. Approx. Reason. 52(7): 948-959 (2011) - [j29]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Classification systems based on rough sets under the belief function framework. Int. J. Approx. Reason. 52(9): 1409-1432 (2011) - [j28]Tianrui Li, Pawan Lingras, Yuefeng Li, Joseph P. Herbert:
Computational Intelligence in Decision Making. Int. J. Comput. Intell. Syst. 4(1) (2011) - [j27]Pawan Lingras, Manish Joshi:
Experimental Comparison of Iterative Versus Evolutionary Crisp and Rough Clustering. Int. J. Comput. Intell. Syst. 4(1): 12-28 (2011) - [j26]Peng Zhang, Manish Joshi, Pawan Lingras:
Use of Stability and Seasonality Analysis for Optimal Inventory Prediction Models. J. Intell. Syst. 20(2): 147-166 (2011) - [j25]Pawan Lingras, Cory J. Butz:
Conservative and aggressive rough SVR modeling. Theor. Comput. Sci. 412(42): 5885-5901 (2011) - [j24]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Classification with Dynamic Reducts and Belief Functions. Trans. Rough Sets 14: 202-233 (2011) - [j23]Pawan Lingras, Georg Peters:
Rough clustering. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 1(1): 64-72 (2011) - [c53]Pawan Lingras, Sarjerao Nimse, N. Darkunde, A. Muley:
Soft clustering from crisp clustering using granulation for mobile call mining. GrC 2011: 410-416 - [c52]Peng Zhang, Manish Joshi, Pawan Lingras:
Clustering of Products to Identify Optimal Inventory Prediction Models. IICAI 2011: 451-464 - [c51]Pawan Lingras, Parag Bhalchandra, Santosh Khamitkar, Satish Mekewad, Ravindra Rathod:
Crisp and Soft Clustering of Mobile Calls. MIWAI 2011: 147-158 - [c50]Sarjerao Nimse, Pawan Lingras:
History of Set Theory and Its Extensions in the Context of Soft Computing. RSKT 2011: 25 - [c49]Pawan Lingras, Parag Bhalchandra, Satish Mekewad, Ravindra Rathod, Santosh Khamitkar:
Comparing Clustering Schemes at Two Levels of Granularity for Mobile Call Mining. RSKT 2011: 696-705 - [e7]Cory J. Butz, Pawan Lingras:
Advances in Artificial Intelligence - 24th Canadian Conference on Artificial Intelligence, Canadian AI 2011, St. John's, Canada, May 25-27, 2011. Proceedings. Lecture Notes in Computer Science 6657, Springer 2011, ISBN 978-3-642-21042-6 [contents] - [e6]Bhanu Prasad, Pawan Lingras, Ramakant Nevatia:
Proceedings of the 5th Indian International Conference on Artificial Intelligence, IICAI 2011, Tumkur, Karnataka State, India, December 14-16, 2011. IICAI 2011, ISBN 978-0-9727412-8-6 [contents] - 2010
- [j22]Pawan Lingras, Cory J. Butz:
Rough support vector regression. Eur. J. Oper. Res. 206(2): 445-455 (2010) - [c48]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Rule Discovery Process Based on Rough Sets under the Belief Function Framework. IPMU 2010: 726-736 - [c47]Manish Joshi, Pawan Lingras, Yiyu Yao, Virendrakumar C. Bhavsar:
Rough, fuzzy, interval clustering for web usage mining. ISDA 2010: 397-402 - [c46]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Belief Rough Set Classification for web mining based on dynamic core. ISDA 2010: 403-408 - [c45]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
A Comparison of Dynamic and Static Belief Rough Set Classifier. RSCTC 2010: 366-375 - [c44]Manish Joshi, Pawan Lingras, C. Raghavendra Rao:
Analysis of Rough and Fuzzy Clustering. RSKT 2010: 679-686 - [p2]Cory J. Butz, Wen Yan, Pawan Lingras, Y. Y. Yao:
The CPT Structure of Variable Elimination in Discrete Bayesian Networks. Advances in Intelligent Information Systems 2010: 245-257 - [e5]Aijun An, Pawan Lingras, Sheila Petty, Runhe Huang:
Active Media Technology, 6th International Conference, AMT 2010, Toronto, Canada, August 28-30, 2010. Proceedings. Lecture Notes in Computer Science 6335, Springer 2010, ISBN 978-3-642-15469-0 [contents] - [e4]Jian Yu, Salvatore Greco, Pawan Lingras, Guoyin Wang, Andrzej Skowron:
Rough Set and Knowledge Technology - 5th International Conference, RSKT 2010, Beijing, China, October 15-17, 2010. Proceedings. Lecture Notes in Computer Science 6401, Springer 2010, ISBN 978-3-642-16247-3 [contents] - [e3]James F. Peters, Andrzej Skowron, Roman Slowinski, Pawan Lingras, Duoqian Miao, Shusaku Tsumoto:
Transactions on Rough Sets XII. Lecture Notes in Computer Science 6190, Springer 2010, ISBN 978-3-642-14466-0 [contents]
2000 – 2009
- 2009
- [j21]Pawan Lingras, Min Chen, Duoqian Miao:
Semi-supervised Rough Cost/Benefit Decisions. Fundam. Informaticae 94(2): 233-244 (2009) - [j20]Cory J. Butz, Junying Chen, Ken Konkel, Pawan Lingras:
A formal comparison of variable elimination and arc reversal in Bayesian network inference. Intell. Decis. Technol. 3(3): 173-180 (2009) - [j19]Pawan Lingras, Min Chen, Duoqian Miao:
Rough Cluster Quality Index Based on Decision Theory. IEEE Trans. Knowl. Data Eng. 21(7): 1014-1026 (2009) - [c43]Pawan Lingras:
Rough K-medoids clustering using GAs. IEEE ICCI 2009: 315-319 - [c42]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Belief Rough Set Classifier. Canadian Conference on AI 2009: 257-261 - [c41]Cory J. Butz, Junying Chen, Ken Konkel, Pawan Lingras:
A Comparative Study of Variable Elimination and Arc Reversal in Bayesian Network Inference. FLAIRS Conference 2009 - [c40]Cory J. Butz, Ken Konkel, Pawan Lingras:
Join Tree Propagation Utilizing Both Arc Reversal and Variable Elimination. FLAIRS Conference 2009 - [c39]Manish Joshi, Virendrakumar C. Bhavsar, Pawan Lingras:
An Algorithm for the Estimation of a Time Period of 2-Sequences. IICAI 2009: 71-88 - [c38]Manish Joshi, Pawan Lingras:
Evolutionary and Iterative Crisp and Rough Clustering I: Theory. PReMI 2009: 615-620 - [c37]Manish Joshi, Pawan Lingras:
Evolutionary and Iterative Crisp and Rough Clustering II: Experiments. PReMI 2009: 621-627 - [c36]Manish Joshi, Rabi N. Bhaumik, Pawan Lingras, Nitin Patil, Ambuja Salgaonkar, Dominik Slezak:
Rough Set Year in India 2009. RSFDGrC 2009: 67-68 - [c35]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Dynamic Reduct from Partially Uncertain Data Using Rough Sets. RSFDGrC 2009: 160-167 - [c34]Yiyu Yao, Pawan Lingras, Ruizhi Wang, Duoqian Miao:
Interval Set Cluster Analysis: A Re-formulation. RSFDGrC 2009: 398-405 - [c33]Pawan Lingras:
Evolutionary Rough K-Means Clustering. RSKT 2009: 68-75 - [e2]Bhanu Prasad, Pawan Lingras, Ashwin Ram:
Proceedings of the 4th Indian International Conference on Artificial Intelligence, IICAI 2009, Tumkur, Karnataka, India, December 16-18, 2009. IICAI 2009, ISBN 978-0-9727412-7-9 [contents] - 2008
- [b1]Rajendra Akerkar, Pawan Lingras:
Building an intelligent web - theory and practice: contains IBM DB2 Express-C9. Jones and Bartlett Publishers 2008, ISBN 978-0-7637-4137-2, pp. I-XI, 1-326 - [c32]Cory J. Butz, Pawan Lingras, Ken Konkel:
A Web-Based Interface for Hiding Bayesian Network Inference. ISMIS 2008: 612-617 - [c31]Pawan Lingras, Min Chen, Duoqian Miao:
Precision of Rough Set Clustering. RSCTC 2008: 369-378 - [c30]Pawan Lingras, Min Chen, Duoqian Miao:
Rough Multi-category Decision Theoretic Framework. RSKT 2008: 676-683 - [p1]Pawan Lingras, Ming Zhong, Satish Sharma:
Evolutionary Regression and Neural Imputations of Missing Values. Soft Computing Applications in Industry 2008: 151-163 - 2007
- [j18]Pawan Lingras, Cory J. Butz:
Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classification. Inf. Sci. 177(18): 3782-3798 (2007) - [j17]Pawan Lingras:
Applications of Rough Set Based K-Means, Kohonen SOM, GA Clustering. Trans. Rough Sets 7: 120-139 (2007) - [c29]Pawan Lingras, Richard Jensen:
Survey of Rough and Fuzzy Hybridization. FUZZ-IEEE 2007: 1-6 - [c28]Pawan Lingras, Rucha Lingras:
Adaptive hyperlinks Using Page Access Sequences and Minimum Spanning Trees. FUZZ-IEEE 2007: 1-6 - [c27]Pawan Lingras, Cory J. Butz:
Precision and Recall in Rough Support Vector Machines. GrC 2007: 654-658 - [c26]Keith Bain, Jason Hines, Pawan Lingras, Yumei Qin:
Using Speech Recognition and Intelligent Search Tools to Enhance Information Accessibility. HCI (7) 2007: 214-223 - [e1]Jingtao Yao, Pawan Lingras, Wei-Zhi Wu, Marcin S. Szczuka, Nick Cercone, Dominik Slezak:
Rough Sets and Knowledge Technology, Second International Conference, RSKT 2007, Toronto, Canada, May 14-16, 2007, Proceedings. Lecture Notes in Computer Science 4481, Springer 2007, ISBN 978-3-540-72457-5 [contents] - 2006
- [c25]Ravipriya Ranatunga, Sisil Kumarawadu, Pawan Lingras, Tsu-Tian Lee:
A New Paradigm for Intelligent Collision Avoidance via Interactive and Interdependent Generic Maneuvers. SMC 2006: 4625-4630 - 2005
- [j16]Pawan Lingras, Xiandong Huang:
Statistical, Evolutionary, and Neurocomputing Clustering Techniques: Cluster-Based vs Object-Based Approaches. Artif. Intell. Rev. 23(1): 3-29 (2005) - [j15]Chad West, Stephanie MacDonald, Pawan Lingras, Greg Adams:
Relationship between Product Based Loyalty and Clustering based on Supermarket Visit and Spending Patterns. Int. J. Comput. Sci. Appl. 2(2): 85-100 (2005) - [j14]Pawan Lingras, Mofreh Hogo, Miroslav Snorek, Chad West:
Temporal analysis of clusters of supermarket customers: conventional versus interval set approach. Inf. Sci. 172(1-2): 215-240 (2005) - [c24]Pawan Lingras, Cory J. Butz:
Interval set representations of 1-v-r support vector machine multi-classifiers. GrC 2005: 193-198 - [c23]Cory J. Butz, Pawan Lingras:
On the Practical Irrelevance of Diverging Implication between Probabilistic Conditional Independence and Embedded Multivalued Dependency. IICAI 2005: 2464-2475 - [c22]Pawan Lingras, Cory J. Butz:
Reducing the Storage Requirements of 1-v-1 Support Vector Machine Multi-classifiers. RSFDGrC (2) 2005: 166-173 - 2004
- [j13]Mofreh Hogo, Miroslav Snorek, Pawan Lingras:
Temporal Versus Latest Snapshot Web Usage Mining Using Kohonen Som And Modified Kohonen Som Based on The Properties of Rough Sets Theory. Int. J. Artif. Intell. Tools 13(3): 569-592 (2004) - [j12]Pawan Lingras, Chad West:
Interval Set Clustering of Web Users with Rough K-Means. J. Intell. Inf. Syst. 23(1): 5-16 (2004) - [j11]Pawan Lingras, Mofreh Hogo, Miroslav Snorek:
Interval set clustering of web users using modified Kohonen self-organizing maps based on the properties of rough sets. Web Intell. Agent Syst. 2(3): 217-225 (2004) - [c21]Ming Zhong, Satish Sharma, Pawan Lingras:
Analyzing the Performance of Genetically Designed Short-Term Traffic Prediction Models Based on Road Types and Functional Classes. IEA/AIE 2004: 1133-1145 - [c20]Pawan Lingras, Mofreh Hogo, Miroslav Snorek:
Temporal Cluster Migration Matrices for Web Usage Mining. Web Intelligence 2004: 441-444 - [c19]Yiyu Yao, Jingtao Yao, Cory J. Butz, Pawan Lingras, Dawn N. Jutla:
Web-based Support Systems (WSS): A Report of the WIC Canada Research Centre. Web Intelligence 2004: 787-788 - 2003
- [j10]Cedric Davies, Pawan Lingras:
Genetic algorithms for rerouting shortest paths in dynamic and stochastic networks. Eur. J. Oper. Res. 144(1): 27-38 (2003) - [c18]Pawan Lingras, Rui Yan, Chad West:
Fuzzy C-Means Clustering of Web Users for Educational Sites. Canadian Conference on AI 2003: 557-562 - [c17]Mofreh Hogo, Pawan Lingras, Miroslav Snorek:
Conventional Versus Interval Clustering Using Kohonen Networks. ICEIS (2) 2003: 250-257 - [c16]Pawan Lingras, Rui Yan, Adish Jain:
Clustering of Web Users: K-Means vs. Fuzzy C-Means. IICAI 2003: 1062-1073 - [c15]Pawan Lingras, Rui Yan, Mofreh Hogo:
Rough Set Based Clustering: Evolutionary, Neural, and Statistical Approaches. IICAI 2003: 1074-1087 - [c14]Chad West, Adish Jain, Pawan Lingras, Bill Leonard:
Supermarket Customer Attrition Analysis Based on Cluster Membership Patterns. IICAI 2003: 1132-1140 - [c13]Pawan Lingras, Mofreh Hogo, Miroslav Snorek, Bill Leonard:
Clustering Supermarket Customers Using Rough Set Based Kohonen Networks. ISMIS 2003: 169-173 - [c12]Pawan Lingras, Rui Yan, Chad West:
Comparison of Conventional and Rough K-Means Clustering. RSFDGrC 2003: 130-137 - [c11]Mofreh Hogo, Miroslav Snorek, Pawan Lingras:
Temporal Web Usage Mining. Web Intelligence 2003: 450-453 - 2002
- [c10]Pawan Lingras:
Rough set clustering for Web mining. FUZZ-IEEE 2002: 1039-1044 - [c9]Pawan Lingras, Y. Y. Yao:
Time Complexity of Rough Clustering: GAs versus K-Means. Rough Sets and Current Trends in Computing 2002: 263-270 - 2001
- [j9]Pawan Lingras, Cedric Davies:
Application of Rough Genetic Algorithms. Comput. Intell. 17(3): 435-445 (2001) - [j8]Pawan Lingras:
Fuzzy-rough and rough-fuzzy serial combinations in neurocomputing. Neurocomputing 36(1-4): 29-44 (2001) - [j7]Pawan Lingras:
Unsupervised Rough Set Classification Using GAs. J. Intell. Inf. Syst. 16(3): 215-228 (2001) - [c8]Pawan Lingras, Paul Mountford:
Time Delay Neural Networks Designed Using Genetic Algorithms for Short Term Inter-City Traffic Forecasting. IEA/AIE 2001: 290-299
1990 – 1999
- 1999
- [c7]