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期刊論文
  1. Z. Ali; T. Mahmood; M.S. Yang , “Weighted Bonferroni aggregation operators with complex q-rung orthopair 2-tuple linguistic variables and their application to green supply chain management” , 2023 , IEEE Access , vol.11 , p.139557-139574. (SCI期刊)
  2. I. Hussain; K.P. Sinaga; M.S. Yang , “Unsupervised multi-view fuzzy c-means clustering” , 2023 , Electronics , vol.12 , p.1-12. (SCI期刊)
  3. T. Mahmood; J. Ahmmad; Z. Ali; M.S. Yang , “Confidence level aggregation operators based on intuitionistic fuzzy rough sets with application in medical diagnosis” , 2023 , IEEE Access , vol.11 , p.8674-8688. (SCI期刊)
  4. X. Wu*; H. Tan; Z. Zhu; L. Liu; G. Chen; M.S. Yang* , “Nonlinear strict distance and similarity measures for intuitionistic fuzzy sets with applications to pattern recognition and medical diagnosis” , 2023 , Scientific Reports , vol.13, article no. 13918 , p.1-17. (SCI期刊)
  5. M.S. Yang*; J.B.M. Benjamin , “Sparse possibilistic c-means clustering with Lasso” , 2023 , Pattern Recognition , vol.138, article no. 109348 , p.1-17. (SCI期刊)
  6. Z. Ali; T. Mahmood; M.S. Yang* , “Frank prioritized aggregation operators and WASPAS method based on complex intuitionistic fuzzy sets and their Application in multi-attribute decision making” , 2023 , Mathematics , vol.11, article no. 2058 , p.1-22. (SCI期刊)
  7. M.S. Yang*; I. Hussain , “Unsupervised multi-view k-means clustering algorithm” , 2023 , IEEE Access , vol.11 , p.13574-13593. (SCI期刊)
  8. M. Riaz; A. Habib; M. Saqlain; M.S. Yang* , “Cubic bipolar fuzzy VIKOR method using new distance and entropy measures and Einstein averaging aggregation operators with application to renewable energy” , 2023 , Int. J. of Fuzzy Systems , vol.25 , p.510-543. (SCI期刊)
  9. Z. Ali; T. Mahmood; M.S. Yang* , “Aczel-Alsina power aggregation operators for complex picture fuzzy (CPF) sets with application in CPF multi-attribute decision making” , 2023 , Symmetry , vol.15, no.3, article no. 651 , p.1-21. (SCI期刊)
  10. W. Ali; M.S. Yang*; M. Ali; S. Ud-Din , “Fuzzy model-based sparse clustering with multivariate t-mixtures” , 2023 , Applied Artificial Intelligence , vol.37, no. 1, e2169299 , p.471-492. (SCI期刊)
  11. M. Ali; Z. Hussain; M.S. Yang* , “Hausdorff distance and similarity measures for single-valued neutrosophic sets with application in multi-criteria decision making” , 2023 , Electronics , vol.12, no. 1, article no. 201 , p.1-17. (SCI期刊)
  12. Z. Hussain; S. Abbas; M.S. Yang* , “Distances and similarity measures of q-rung orthopair fuzzy sets based on the Hausdorff metric with the construction of orthopair fuzzy TODIM” , 2022 , Symmetry , vol.14, no. 11, article no. 2467 , p.1-22. (SCI期刊)
  13. J.B.M. Benjamin; M.S. Yang* , “Weighted multiview possibilistic c-means clustering with L2 regularization” , 2022 , IEEE Transactions on Fuzzy Systems , vol.30, no. 5 , p.1357-1370. (SCI期刊)
  14. A. Hussain; K. Ullah; M.N. Alshahrani; M.S. Yang*; D. Pamucar , “Novel Aczel-Alsina operators for Pythagorean fuzzy sets with application in multi-attribute decision making” , 2022 , Symmetry , vol.14, no. 5, article no. 940 , p.1-12. (SCI期刊)
  15. A. Nasir; N. Jan; M.S. Yang*; D. Pamucar; D. Marinkovic; S.U. Khan , “Security risks to petroleum industry: An innovative modeling technique based on novel concepts of complex bipolar fuzzy information” , 2022 , Mathematics , vol.10, no. 7, article no. 1067 , p.1-28. (SCI期刊)
  16. A. Khan; M.S. Yang*; M. Haq; A.A. Shah; M. Arif , “A new approach for normal parameter reduction using σ-algebraic soft sets and its application in multi-attribute decision making” , 2022 , Mathematics , vol.10, no. 8, article no. 1297 , p.1-17. (SCI期刊)
  17. A. Hussain; K. Ullah; M.S. Yang*; D. Pamucar , “Aczel-Alsina aggregation operators on T-spherical fuzzy (TSF) information with application to TSF multi-attribute decision making” , 2022 , IEEE Access , vol.10 , p.26011-26023. (SCI期刊)
  18. M.N. Abid; M.S. Yang*; H. Karamti; K. Ullah; D. Pamucar , “Similarity measures based on T-spherical fuzzy information with applications to pattern recognition and decision making” , 2022 , Symmetry , vol.14, no. 2, article no. 410 , p.1-16. (SCI期刊)
  19. M.S. Yang*; K.P. Sinaga , “Collaborative feature-weighted multi-view fuzzy c-means clustering” , 2021 , Pattern Recognition , vol.119, article no. 108064 , p.1-15. (SCI期刊)
  20. M.N. Jafar; M. Saeed; M. Saqlain; M.S. Yang* , “Trigonometric similarity measures for neutrosophic hypersoft sets with application to renewable energy source selection” , 2021 , IEEE Access , vol.9 , p.129178-129187. (SCI期刊)
  21. A. Nasir; N. Jan; M.S. Yang*; S.U. Khan , “Complex T-spherical fuzzy relations with their applications in economic relationships and international trades” , 2021 , IEEE Access , vol.9 , p.66115-66131. (SCI期刊)
  22. J. Hua*; J. Yu; M.S. Yang* , “Star-based learning correlation clustering” , 2021 , Pattern Recognition , vol.116, article no. 107966 , p.1-11. (SCI期刊)
  23. M.S. Yang*; Z. Ali; T. Mahmood , “Three-way decisions based on q-rung orthopair fuzzy 2-tuple linguistic sets with generalized Maclaurin symmetric mean operators” , 2021 , Mathematics , vol.9 , p.1-20. (SCI期刊)
  24. M.S. Yang*; J.B.M. Benjamin , “Feature-weighted possibilistic c-means clustering with a feature-reduction framework” , 2021 , IEEE Transactions on Fuzzy Systems , vol.29 , p.1093-1106. (SCI期刊)
  25. K.P. Sinaga; I. Hussian; M.S. Yang* , “Entropy k-means clustering with feature reduction under unknown number of clusters” , 2021 , IEEE Access , vol.9 , p.67736-67751. (SCI期刊)
  26. S.J. Chang-Chien; Y. Nataliani; M.S. Yang* , “Gaussian-kernel c-means clustering algorithms” , 2021 , Soft Computing , vol.25(3) , p.1699-1716. (SCI期刊)
  27. M.S. Yang*; Z. Ali; T. Mahmood , “Complex q-rung orthopair uncertain linguistic partitioned Bonferroni mean operators with application in antivirus mask selection” , 2021 , Symmetry , vol.13 (2), Article No. 249 , p.1-23. (SCI期刊)
  28. M.R. Ahmad; M. Saeed; U. Afzal; M.S. Yang* , “A novel MCDM method based on plithogenic hypersoft sets under fuzzy neutrosophic environment” , 2020 , Symmetry , vol.12, Article No. 1855 , p.1-23. (SCI期刊)
  29. Z. Ali; T. Mahmood; M.S. Yang* , “TOPSIS method based on complex spherical fuzzy sets with Bonferroni mean operators” , 2020 , Mathematics , vol.8, Article No. 1739 , p.1-19. (SCI期刊)
  30. Z. Ali; T. Mahmood; M.S. Yang* , “Complex t-spherical fuzzy aggregation operators with application to multi-attribute decision making ” , 2020 , Symmetry , vol.12 (8), Article No. 1311 , p.1-25. (SCI期刊)
  31. M.S. Yang*; Z. Hussian; M. Ali , “Belief and plausibility measures on intuitionistic fuzzy sets with construction of belief-plausibility TOPSIS” , 2020 , Complexity , vol.2020, Article No. 7849686 , p.1-12. (SCI期刊)
  32. K.P. Sinaga; M.S. Yang* , “Unsupervised k-means clustering algorithm” , 2020 , IEEE Access , vol.8 , p.80716-80727. (SCI期刊)
  33. J. Hua*; J. Yu; M.S. Yang* , “Fast clustering for signed graphs based on random walk gap” , 2020 , Social Networks , vol.60 , p.113-128. (SSCI期刊)
  34. M.S. Yang*; W. Ali , “Fuzzy Gaussian Lasso clustering with application to cancer data” , 2020 , Mathematical Bioscience and Engineering , vol.17 , p.250-265. (SCI期刊)
  35. M.S. Yang*; K.P. Sinaga , “A feature-reduction multi-view k-means clustering algorithm” , 2019 , IEEE Access , vol.7 , p.114472-114486. (SCI期刊)
  36. Z. Hussian; M.S. Yang* , “Distance and similarity measures of Pythagorean fuzzy sets based on Hausdorff metric with application to fuzzy TOPSIS” , 2019 , International Journal of Intelligent Systems , vol.34 , p.2633-2654. (SCI期刊)
  37. M.S. Yang*; S.J. Chang-Chien; Y. Nataliani , “Unsupervised fuzzy model-based Gaussian clustering” , 2019 , Information Sciences , vol.481 , p.1-23. (SCI期刊)
  38. Y. Nataliani; M.S. Yang* , “Powered Gaussian kernel spectral clustering” , 2019 , Neural Computing and Applications , vol.31, Supplement 1 , p.557-572. (SCI期刊)
  39. M.S. Yang*; S.J. Chang-Chien; Y. Nataliani , “A fully-unsupervised possibilistic c-means clustering method” , 2018 , IEEE Access , vol.6 , p.78308-78320. (SCI期刊)
  40. M.S. Yang*; Z. Hussian , “Fuzzy entropy for Pythagorean fuzzy sets with application to multicriterion decision making” , 2018 , Complexity , vol.2018, Article ID 2832839 , p.1-14. (SCI期刊)
  41. Z. Hussian; M.S. Yang* , “Entropy for hesitant fuzzy sets based on Hausdorff metric with construction of hesitant fuzzy TOPSIS” , 2018 , International Journal of Fuzzy Systems , vol.20 , p.2517-2533. (SCI期刊)
  42. C.M. Hwang; M.S. Yang*; W.L. Hung , “New similarity measures of intuitionistic fuzzy sets based on the Jaccard index with its application to clustering” , 2018 , International Journal of Intelligent Systems , vol.33 , p.1672-1688. (SCI期刊)
  43. M.S. Yang*; Y. Nataliani , “A feature-reduction fuzzy clustering algorithm with feature-weighted entropy” , 2018 , IEEE Transactions on Fuzzy Systems , vol.26 , p.817-835. (SCI期刊)
  44. M.S. Yang*; C.C. Yeh , “Fuzzy generalization and comparisons for the Rand index” , 2018 , International Journal of Intelligent Systems , vol.33 , p.901-927. (SCI期刊)
  45. J. Yu; C. Chaomurilige; M.S. Yang* , “On convergence and parameter selection of the EM and DA-EM algorithms for Gaussian mixtures” , 2018 , Pattern Recognition , vol.77 , p.188-203. (SCI期刊)
  46. Chaomurilige; J. Yu*; M.S. Yang* , “Deterministic annealing Gustafson-Kessel fuzzy clustering algorithm” , 2017 , Information Sciences , vol.417 , p.435-453. (SCI期刊)
  47. M.S. Yang*; S.J. Chang-Chien; W.L. Hung , “Learning-based EM clustering for data on the unit hypersphere with application to exoplanet data” , 2017 , Applied Soft Computing , vol.60 , p.101-114. (SCI期刊)
  48. M.S. Yang*; Y. Nataliani , “Robust-learning fuzzy c-means clustering algorithm with unknown number of clusters” , 2017 , Pattern Recognition , vol.71 , p.45-59. (SCI期刊)
  49. Y. Nataliani; M.S. Yang* , “Spectral clustering for cell formation with minimum dissimilarities distance” , 2017 , Lecture Notes in Computer Science , vol.10246 , p.126-136. (EI期刊)
  50. C.C. Yeh; M.S. Yang* , “Evaluation measures for cluster ensembles based on a fuzzy generalized Rand index” , 2017 , Applied Soft Computing , vol.57 , p.225-234. (SCI期刊)
  51. C.M. Hwang; M.S. Yang* , “Belief and plausibility functions on intuitionistic fuzzy set” , 2016 , International Journal of Intelligent Systems , vol.31 , p.556-568. (SCI期刊)
  52. M.S. Yang*; S.J. Chang-Chien; W.L. Hung , “An unsupervised clustering algorithm for data on the unit hypersphere” , 2016 , Applied Soft Computing , vol.42 , p.290-313. (SCI期刊)
  53. C.C. Yeh; M.S. Yang* , “A generalization of Rand and Jaccard indices with its fuzzy extension” , 2016 , International Journal of Fuzzy Systems , vol.18 , p.1008-1018. (SCI期刊)
  54. S.T Chang; K.P. Lu; M.S. Yang* , “Stepwise possibilistic c-regressions” , 2016 , Information Sciences , vol.334-335 , p.307-322. (SCI期刊)
  55. K.P. Lu; S.T Chang*; M.S. Yang , “Change-point detection for shifts in control charts using fuzzy shift change-point algorithms” , 2016 , Computers & Industrial Engineering , vol.93 , p.12-27. (SCI期刊)
  56. S.T Chang; K.P. Lu; M.S. Yang* , “Fuzzy change-point algorithms for regression models” , 2015 , IEEE Transactions on Fuzzy Systems , vol.23 , p.2343-2357. (SCI期刊)
  57. Chaomurilige; J. Yu*; M.S. Yang* , “Analysis of parameter selection for Gustafson-Kessel fuzzy clustering using Jacobian matrix” , 2015 , IEEE Transactions on Fuzzy Systems , vol.23 , p.2329-2342. (SCI期刊)
  58. C.N. Wang; M.S. Yang* , “Cluster analysis based on T-transitive interval-valued fuzzy relations” , 2015 , International Journal of Intelligent Systems , vol.30 , p.1083-1100. (SCI期刊)
  59. W.L. Hung*; S.J. Chang-Chien; M.S. Yang , “An intuitive clustering algorithm for spherical data with application to extrasolar planets” , 2015 , Journal of Applied Statistics , vol.42 , p.2220-2232. (SCI期刊)
  60. M.S. Yang*; C.N. Wang , “Clustering methods based on weighted quasi-arithmetic means of T-transitive fuzzy relations” , 2015 , International Journal of Uncertainty Fuzziness and Knowledge-Based Systems , vol.23 , p.715-733. (SCI期刊)
  61. M.S. Yang*; Y.C. Tian , “Bias-correction fuzzy clustering algorithms” , 2015 , Information Sciences , vol.309 , p.138-162. (SCI期刊)
  62. Y. Nataliani; C.M. Hwang; M.S. Yang* , “An exponential-type entropy measure on intuitionistic fuzzy sets” , 2015 , Lecture Notes in Computer Science , vol.LNAI 9119 , p.218-227. (EI期刊)
  63. C.M. Hwang; M.S. Yang* , “New similarity measures between generalized trapezoidal fuzzy numbers using the Jaccard index” , 2014 , International Journal of Uncertainty Fuzziness and Knowledge-Based Systems , vol.22 , p.831-844. (SCI期刊)
  64. M.S. Yang*; Y.C. Tian; C.Y. Lin , “Robust fuzzy classification maximum likelihood clustering with multivariate t-distributions” , 2014 , International Journal of Fuzzy Systems , vol.16 , p.566-576. (SCI期刊)
  65. H.C. Kuo; M.S. Yang*; J.H. Yang; Y.C. Chen , “SCM-Driven Tree View for Microarray Data” , 2014 , Lecture Notes in Computer Science , vol.LNAI 8468 , p.207-215. (EI期刊)
  66. M.S. Yang*; S.J. Chang-Chien; H.C. Kuo , “On Mean Shift Clustering for Directional Data on a Hypersphere” , 2014 , Lecture Notes in Computer Science , vol.LNAI 8468 , p.809-818. (EI期刊)
  67. M.S. Yang*; C.Y. Lin; Y.C. Tian , “A robust fuzzy classification maximum likelihood clustering framework” , 2013 , International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems , vol.21 , p.755-776. (SCI期刊)
  68. C.M. Hwang; M.S. Yang* , “New construction for similarity measures between intuitionistic fuzzy sets based on lower, upper and middle fuzzy sets” , 2013 , International Journal of Fuzzy Systems , vol.15 , p.371-378. (SCI期刊)
  69. J. Yu; M.S. Yang*; P. Hao , “Clustering construction on a multimodal probability model” , 2013 , Information Sciences , vol.237 , p.211-220. (SCI期刊)
  70. M.S. Yang*; C.Y. Lai; C.Y. Lin , “A robust EM clustering algorithm for Gaussian mixture models” , 2012 , Pattern Recognition , vol.45 , p.3950-3961. (SCI期刊)
  71. W.L. Hung*; S.J. Chang-Chien; M.S. Yang , “Self-updating clustering algorithm for estimating the parameters in mixtures of von Mises distributions” , 2012 , Journal of Applied Statistics , vol.39 , p. 2259-2274. (SCI期刊)
  72. C.M. Hwang; M.S. Yang* , “Modified cosine similarity measure between intuitionistic fuzzy sets” , 2012 , Lecture Notes in Computer Science , vol.LNAI 7530 , p.285-293. (EI期刊)
  73. M.S. Yang*; W.L. Hung; D.H. Chen , “Self-organizing map for symbolic data” , 2012 , Fuzzy Sets and Systems , vol.203 , p.49-73. (SCI期刊)
  74. S..J. Chang-Chien; W.L. Hung; M.S. Yang* , “On mean shift-based clustering for circular data” , 2012 , Soft Computing , vol.16 , p.1043-1060. (SCI期刊)
  75. C.M. Hwang; M.S. Yang*; W.L. Hung , “On similarity, inclusion measure and entropy between type-2 fuzzy sets” , 2012 , International Journal of Uncertainty Fuzziness and Knowledge-Based Systems , vol.20 , p.433-449. (SCI期刊)
  76. C.M. Hwang; M.S. Yang*; W.L. Hung; M.G. Lee , “A similarity measure of intuitionistic fuzzy sets based on Sugeno integral with its application to pattern recognition” , 2012 , Information Sciences , vol.189 , p.93-109. (SCI期刊)
  77. J. Yu; M.S. Yang*; E.S. Lee , “Sample-weighted clustering methods” , 2011 , Computers and Mathematics with Applications , vol.62 , p.2200-2208. (SCI期刊)
  78. C.M. Hwang; M.S. Yang*; W.L. Hung; E.S. Lee , “Similarity, inclusion and entropy measures between type-2 fuzzy sets based on the Sugeno integral” , 2011 , Mathematical and Computer Modelling , vol.53 , p.1788-1797. (SCI期刊)
  79. W.L. Hung*; M.S. Yang; E.S. Lee , “Cell formation using fuzzy relational clustering algorithm” , 2011 , Mathematical and Computer Modelling , vol.53 , p.1776-1787. (SCI期刊)
  80. W.L. Hung*; D.H. Chen; M.S. Yang , “Suppressed fuzzy-soft learning vector quantization for MRI segmentation” , 2011 , Artificial Intelligence in Medicine , vol.52 , p.33-43. (SCI期刊)
  81. C.Y. Lai; M.S. Yang* , “Entropy-type classification maximum likelihood algorithms for mixture models ” , 2011 , Soft Computing , vol.15 , p.373-381. (SCI期刊)
  82. M.S. Yang*; C.Y Lai , “A Robust Automatic Merging Possibilistic Clustering Method” , 2011 , IEEE Trans. on Fuzzy Systems , vol.19 , p.26-41. (SCI期刊)
  83. C.M. Hwang; M.S. Yang* , “On fuzzy renewal processes for fuzzy random variables and extended theorems” , 2011 , International Journal of Intelligent Systems , vol.26 , p.115-128. (SCI期刊)
  84. J. Yu*; M.S. Yang; P. Hao , “A novel multimodal probability model for cluster analysis” , 2011 , Fundamenta Informaticae , vol.111 , p.81-90. (SCI期刊)
  85. M.S. Yang*; K.L. Wu; K.C.R. Lin; H.C. Liu; J.F. Lirng , “On three types of competitive learning algorithms with their comparisons and applications to MRI segmentation” , 2010 , International Journal of Intelligent Systems , vol.25 , p.1081-1102. (SCI期刊)
  86. W.L. Hung; M.S. Yang*; E.S. Lee , “A robust clustering procedure for fuzzy data” , 2010 , Computers and Mathematics with Applications , vol.60 , p.151-165. (SCI期刊)
  87. W.L. Hung; M.S. Yang*; J. Yu; C.M. Hwang , “Feature-weighted mountain method with its applications to color image segmentation” , 2010 , Lecture Notes in Computer Science , vol.LNAI 6401 , p.537-544. (EI期刊)
  88. K.L. Wu; M.S. Yang*; J.N. Hsieh , “Mountain c-regressions method” , 2010 , Pattern Recognition , vol.43 , p.86-98. (SCI期刊)
  89. R.W. Po; Y.Y. Guh*; M.S. Yang , “A new clustering approach using data envelopment analysis” , 2009 , European Journal of Operational Research , vol.199 , p.276-284. (SCI期刊)
  90. K.L. Wu*; M.S. Yang; J.N. Hsieh , “Robust cluster validity indexes” , 2009 , Pattern Recognition , vol.42 , p.2541-2550. (SCI期刊)
  91. Y.Y. Guh*; M.S. Yang; R.W. Po; E.S. Lee , “Interval-valued fuzzy relation-based clustering with its application to performance evaluation” , 2009 , Computers and Mathematics with Applications , vol.57 , p.841-849. (SCI期刊)
  92. M.S. Yang*; D.C. Lin , “On similarity and inclusion measures between type-2 fuzzy sets with an application to clustering” , 2009 , Computers and Mathematics with Applications , vol.57 , p.896-907. (SCI期刊)
  93. M.S. Yang*; H.S.Tsai , “A Gaussian kernel-based fuzzy c-means algorithm with a spatial bias correction” , 2008 , Pattern Recognition Letters , vol.29 , p.1713-1725. (SCI期刊)
  94. C.M. Hwang; M.S. Yang* , “On entropy of fuzzy sets” , 2008 , Int. J. of Uncertainty, Fuzziness and Knowledge-Based Systems , vol.16 , p.519-527. (SCI期刊)
  95. M. S. Yang*; J. H. Yang , “Machine-part cell formation in group technology using a modified ART1 method” , 2008 , European Journal of Operational Research , vol.188 , p.140-152. (SCI期刊)
  96. W.L. Hung*; M.S. Yang; D.H. Chen , “Bootstrapping approach to feature-weight selection in fuzzy c-means algorithms with an application in color image segmentation” , 2008 , Pattern Recognition Letters , vol.29 , p.1317-1325. (SCI期刊)
  97. Y.Y. Guh*; M.S. Yang; R.W. Po; E.S. Lee , “Establishing performance evaluation structures by fuzzy relation-based cluster analysis” , 2008 , Computers and Mathematics with Applications , vol.56 , p.572-582. (SCI期刊)
  98. M.S. Yang*; K.L. Wu; J.N. Hsieh; J. Yu , “Alpha-cut implemented fuzzy clustering algorithms and switching regressions” , 2008 , IEEE Transactions on Systems, Man, and Cybernetics-Part B , vol.38 , p.588-603. (SCI期刊)
  99. W.L. Hung*; M.S. Yang , “On the j-divergence of intuitionistic fuzzy sets with its application to pattern recognition” , 2008 , Information Sciences , vol.178 , p.1641-1650. (SCI期刊)
  100. W.L. Hung; M.S. Yang* , “On similarity measures between intuitionistic fuzzy sets” , 2008 , International Journal of Intelligent Systems , vol. 23 , p.364-383. (SCI期刊)
  101. M.S. Yang*; Y.H. Chiang; C.C. Chen; C.Y. Lai , “A fuzzy k-partitions model for categorical data and its comparison to the GoM model” , 2008 , Fuzzy Sets and Systems , vol.159 , p.390-405 . (SCI期刊)
  102. C.M. Hwang; M.S. Yang* , “Generalization of belief and plausibility functions to fuzzy sets based on Sugeno integral” , 2007 , International Journal of Intelligent Systems , vol.22 , p.1215-1228. (SCI期刊)
  103. K.L. Wu; M.S. Yang* , “Mean shift-based clustering” , 2007 , Pattern Recognition , vol.40 , p.3035-3052. (SCI期刊)
  104. J. Yu; M.S. Yang* , “A generalized fuzzy clustering regularization model with optimality tests and model complexity analysis” , 2007 , IEEE Trans. on Fuzzy Systems , vol.15 , p.904-915. (SCI期刊)
  105. W.L. Hung*; M.S. Yang , “Similarity measures of intuitionistic fuzzy sets based on Lp metric” , 2007 , International Journal of Approximate Reasoning , vol.46 , p.120-136. (SCI期刊)
  106. M.S. Yang*; K.C.R. Lin; H.C. Lin; J.F. Lirng , “Magnetic resonance imaging segmentation techniques using batch-type learning vector quantization algorithms” , 2007 , Magnetic Resonance Imaging , vol.25 , p.265-277. (SCI期刊)
  107. W.L. Hung*, M.S. Yang , “An omission approach for detecting outliers in fuzzy regression models” , 2006 , Fuzzy Sets and Systems , vol.157 , p.3109-3122. (SCI期刊)
  108. M.S. Yang*, W.L. Hung, F.J. Cheng , “Mixed-variable fuzzy clustering approach to part family and machine cell formation for GT applications” , 2006 , International Journal of Production Economics , vol.103 , p.185-198. (SCI期刊)
  109. I.G. Jiang*, L.C. Yeh, W.L. Hung, M.S. Yang , “Data analysis on the extrasolar planets using robust clustering ” , 2006 , Monthly Notices of the Royal Astronomical Society , vol.370 , p.1379-1392. (SCI期刊)
  110. W.L. Hung, M.S. Yang* , “Fuzzy entropy on intuitionistic fuzzy sets” , 2006 , International Journal of Intelligent Systems , vol.21 , p.443-451. (SCI期刊)
  111. W.L. Hung*, M.S. Yang and D.H. Chen , “Parameter selection for suppressed fuzzy c-means with an application to MRI segmentation” , 2006 , Pattern Recognition Letters , vol.27 , p.424-438. (SCI期刊)
  112. K.L. Wu, M.S. Yang* , “Alternative learning vector quantization” , 2006 , Pattern Recognition , vol.39 , p.351-362. (SCI期刊)
  113. M.S. Yang*; W.L. Hung, C.H. Chang , “A penalized fuzzy clustering algorithm” , 2006 , WSEAS Trans. on Computers Research , vol.1 , p.83-88.
  114. M.S. Yang*; W..L. Hung; T.I. Chung , “Alternative fuzzy c-means clustering algorithms with L1-norm and covariance matrix” , 2006 , Lecture Notes in Computer Science , vol.LNCS 4179 , p.654-665.
  115. M.S. Yang*, K.L. Wu , “Unsupervised possibilistic clustering” , 2006 , Pattern Recognition , vol.39 , p.5-21. (SCI期刊)
  116. M.S. Yang*, W.L. Hung and S.J. Chang-Chien , “On a similarity measure between LR-type fuzzy numbers and its application to database acquisition” , 2005 , International Journal of Intelligent Systems , vol.20 , p.1001-1016. (SCI期刊)
  117. K.L. Wu and M.S. Yang* , “A cluster validity index for fuzzy clustering” , 2005 , Pattern Recognition Letters , vol.26 , p.1275-1291. (SCI期刊)
  118. M.S. Yang* and K.L. Wu , “A modified mountain clustering algorithm” , 2005 , Pattern Analysis and Applications , vol.8 , p.125-138. (SCI期刊)
  119. M.S. Yang* and C.Y. Lai , “Mixture Poisson regression models for heterogeneous count data based on latent and fuzzy class analysis” , 2005 , Soft Computing , vol.9 , p.519-524. (SCI期刊)
  120. J. Yu and M.S. Yang* , “A note on the ICS algorithm with corrections and theoretical analysis” , 2005 , IEEE Trans. on Image Processing , vol.14 , p.973-978. (SCI期刊)
  121. M.S. Yang*; H.S. Tsai , “An alternative fuzzy compactness and separation clustering algorithm” , 2005 , Lecture Notes in Computer Science, , vol.LNCS 3708 , p.146-153. (EI期刊)
  122. K.L. Wu, J. Yu and M.S. Yang* , “A novel fuzzy clustering algorithm based on a fuzzy scatter matrix with optimality tests” , 2005 , Pattern Recognition Letters , vol.26 , p.639-652. (SCI期刊)
  123. J.H. Yang and M.S. Yang* , “A control chart pattern recognition system using a statistical correlation coefficient method” , 2005 , Computers & Industrial Engineering , vol.48 , p.205-221. (SCI期刊)
  124. W.L. Hung and M.S. Yang* , “Fuzzy clustering on LR-type fuzzy numbers with an application in Taiwanese tea evaluation” , 2005 , Fuzzy Sets and Systems , vol.150 , p.561-577. (SCI期刊)
  125. J. Yu and M.S. Yang* , “Optimality test for generalized FCM and its application to parameter selection” , 2005 , IEEE Trans. on Fuzzy Systems , vol.13 , p.164-176. (SCI期刊)
  126. M.S. Yang* and N.Y. Yu , “Estimation of parameters in latent class models using fuzzy clustering algorithms” , 2005 , European Journal of Operational Research , vol.160 , p.515-531. (SCI期刊)
  127. W.L. Hung* and M.S. Yang , “Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance” , 2004 , Pattern Recognition Letters , vol.25 , p.1603-1611. (SCI期刊)
  128. W.L. Hung and M.S. Yang* , “Similarity measures between type-2 fuzzy sets” , 2004 , Int. J. of Uncertainty, Fuzziness and Knowledge-Based Systems , vol.12 , p.827-841. (SCI期刊)
  129. M.S. Yang* and H.M. Chen , “Fuzzy class logistic regression analysis” , 2004 , Int. J. of Uncertainty, Fuzziness and Knowledge-Based Systems , vol.12 , p.761-780. (SCI期刊)
  130. M.S. Yang* and K. L. Wu , “A similarity-based robust clustering method” , 2004 , IEEE Trans. on Pattern Analysis and Machine Intelligence , vol.26 , p.434-448. (SCI期刊)
  131. Y.Y. Hong*, Z.T. Chao and M.S. Yang , “A fuzzy multiple linear regression based loss formula in electric distribution systems” , 2004 , Fuzzy Sets and Systems , vol.142 , p.293-306. (SCI期刊)
  132. M.S. Yang*, P. Y. Hwang and D.H. Chen , “Fuzzy clustering algorithms for mixed feature variables” , 2004 , Fuzzy Sets and Systems , vol.141 , p.301-317. (SCI期刊)
  133. K.L. Wu and M.S. Yang* , “A fuzzy-soft learning vector quantization” , 2003 , Neurocomputing , vol.55 , p.681-697. (SCI期刊)
  134. K.C.R. Lin, M.S. Yang*, H.C. Liu, J.F. Lirng and P.N. Wang , “Generalized Kohonen’s competitive learning algorithms for ophthalmological MR image segmentation” , 2003 , Magnetic Resonance Imaging , vol.21 , p.863-870. (SCI期刊)
  135. M.S. Yang*, T.C. Chen and K.L. Wu , “Generalized belief function, plausibility function, and Dempster’s combinational rule to fuzzy sets” , 2003 , International Journal of Intelligent Systems , vol.18 , p.925-937. (SCI期刊)
  136. M.S. Yang*, H.H. Liu , “Fuzzy least-square algorithms for interactive fuzzy linear regression models” , 2003 , Fuzzy Sets and Systems , vol.135 , p.305-316. (SCI期刊)
  137. K.L. Wu and M.S. Yang* , “Alternative c-means clustering algorithms” , 2002 , Pattern Recognition , vol.35 , p.2267-2278. (SCI期刊)
  138. M.S. Yang*; J.H. Yang , “A fuzzy-soft learning vector quantization for control chart pattern recognition” , 2002 , International Journal of Production Research , vol.40 , p.2721-2731. (SCI期刊)
  139. M.S. Yang*; T.S. Lin , “Fuzzy least-square linear regression analysis for fuzzy input-output data” , 2002 , Fuzzy Sets and Systems , vol.126 , p.389-399. (SCI期刊)
  140. M.S.Yang*; Y.J.Hu; K.C.R. Lin; C.C.L Lin , “Segmentation techniques for tissue differentiation in MRI of Ophthalmology using fuzzy clustering algorithms” , 2002 , Magnetic Resonance Imaging , vol.20 , p.173-179. (SCI期刊)
  141. M.S. Yang*; H.M. Shih , “Cluster analysis based on fuzzy relations” , 2001 , Fuzzy Sets and Systems , vol.120 , p.197-212. (SCI期刊)
  142. M.S. Yang*; H.H. Liu , “Fuzzy clustering procedures for conical fuzzy vector data” , 1999 , Fuzzy Sets and Systems , vol.106 , p.189-200. (SCI期刊)
  143. M.S. Yang*; C.H. Chen , “On the edited fuzzy k-nearest neighbor rule” , 1998 , IEEE Trans, On Systems, Man and Cybernetics--PartB , vol.28 , p.461-466. (SCI期刊)
  144. M.S Yang*; M.C Liu , “On possibility analysis of fuzzy data” , 1998 , Fuzzy Sets and Systems , vol.94 , p.171-183. (SCI期刊)
  145. M.S. Yang*; J.A. Pan , “ On fuzzy clustering of directional data” , 1997 , Fuzzy Sets and Systems , vol.91 , p.319-326. (SCI期刊)
  146. M.S. Yang*; C.H. Ko , “On cluster-wise fuzzy regression analysis” , 1997 , IEEE Trans. on Systems, Man, and Cybernetics-Part B , vol.27 , p.1-13. (SCI期刊)
  147. M.S. Yang*; C.H. Ko , “On a class of fuzzy c-numbers clustering procedures for fuzzy data” , 1996 , Fuzzy Sets and Systems , vol.84 , p.49-60. (SCI期刊)
  148. M.S. Yang*; C.F. Su , “On parameter estimation for normal mixtures based on fuzzy clustering algorithms” , 1994 , Fuzzy Sets and Systems , vol.68 , p.13-28. (SCI期刊)
  149. M.S. Yang* , “On asymptotic normality of a class of fuzzy c-means clustering procedures” , 1994 , Int. J. of General Systems , vol.22 , p.391-403. (SCI期刊)
  150. M.S. Yang*; C.T. Chen , “Convergence rate of the fuzzy generalized nearest neighbor rule” , 1994 , Computers and Mathematics with Application , vol.27 , p.1-8. (SCI期刊)
  151. M.S. Yang* , “A survey of fuzzy clustering ” , 1993 , Mathematical and Computer Modeling , vol.18 , p.1-16. (SCI期刊)
  152. M.S. Yang*; C.T. Chen , “On strong consistency of the fuzzy generalized nearest neighbor rule” , 1993 , Fuzzy Sets and Systems , vol.60 , p.273-281. (SCI期刊)
  153. M.S. Yang* , “On a class of fuzzy classification maximum likelihood procedures” , 1993 , Fuzzy Sets and Systems , vol.57 , p.365-375. (SCI期刊)
  154. M.S. Yang* , “Convergence properties of the generalized fuzzy c-means clustering algorithms” , 1993 , Computers and Mathematics with Applications , vol.25 , p.3-11. (SCI期刊)
  155. M.S. Yang*; K.F. Yu , “On existence and strong consistency of a class of fuzzy c-means clustering procedures” , 1992 , Cybernetics and Systems , vol.23 , p.583-602. (SCI期刊)
  156. M.S. Yang*; K.F. Yu , “On stochastic convergence theorems for the fuzzy c-means clustering procedures” , 1990 , Int. J. of General Systems , vol.16 , p.397-411. (SCI期刊)
研討會論文
  1. M.S. Yang; S.J. Chang-Chien; Y. Akhtar , “Gaussian-kernel neutrosophic c-means clustering” , 2023 , Future Technologies Conference (FTC) 2023 , 2023 /11 /2 ~ 2023 /11 /3 , United States .
  2. M.S. Yang , “Sparse possibilistic c-means clustering with Lasso” , 2023 , The 2023 International Experts Summit on Artificial Intelligence and Robotic Technology, IESAIRT 2023 (Invited plenary speaker) , 2023 /9 /7 ~ 2023 /9 /8 , Japan .
  3. J.B. Benjamin; S. Parveen; M.S. Yang , “Sparse weighted multi-view possibilistic c-means clustering with L1 regularization” , 2022 , The 2022 International Conference on Intelligent and Fuzzy Systems, INFUS 2022 , 2022 /7 /19 ~ 2022 /7 /21 , Republic of Turkey .
  4. W. Ali; I. Hussian; M.S. Yang , “Fuzzy model-based robust clustering with multivariate t-mixture distributions” , 2021 , The 2021 4th International Conference on Computational Intelligence and Data Engineering (ICCIDE’21) , 2021 /8 /13 ~ 2021 /8 /14 , Republic of India .
  5. J.N. Hsieh; M. Ali; M.S. Yang , “Subtractive clustering for categorical data with a novel separation difference validity index” , 2020 , The 2020 16th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD’20) , 2020 /12 /19 ~ 2020 /12 /21 , 大陸地區 .
  6. M.S. Yang , “A feature-reduction fuzzy c-means clustering algorithm” , 2020 , The 6th International Conference on Basic Sciences, ICBS-2020 (Keynote Speaker) , 2020 /11 /4 ~ 2020 /11 /5 , Republic of Indonesia .
  7. J.B.M. Benjamin; I. Hussain; M.S. Yang , “Possibilistic c-means clustering on directional data” , 2019 , Proceedings of the 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI 2019) , 2019 /10 /19 ~ 2019 /10 /21 , 大陸地區 .
  8. Y. Nataliani; M.S. Yang , “Feature-weighted fuzzy k-modes clustering” , 2019 , Proceedings of the 2019 3rd International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (ISMSI 2019) , 2019 /3 /23 ~ 2019 /3 /24 , Republic of Maldives .
  9. M.S. Yang; S.J. Chang-Chien; Y. Nataliani , “Gaussian-kernel c-means clustering algorithms” , 2018 , Proceedings of the 7th International Conference on Theory and Practice of Natural Computing, TPNC-2018 , 2018 /12 /12 ~ 2018 /12 /14 , Republic of Ireland .
  10. S.J. Chang-Chien; M.S. Yang; Wajid Ali , “A learning-based EM clustering for circular data with unknown number of clusters” , 2018 , Proceedings of the International Conference on Advanced Technology Innovation 2018 (ICATI-2018) , 2018 /6 /27 ~ 2018 /6 /30 , Thailand .
  11. K.P. Sinaga; J.N. Hsieh; J.B.M. Benjamin; M.S. Yang , “Modified relational mountain clustering method” , 2018 , The 2018 International Conference on Artificial Intelligence and Soft Computing (ICAISC 2018) , 2018 /6 /3 ~ 2018 /6 /7 , Republic of Poland .
  12. Y. Nataliani; M.S. Yang , “Spectral clustering for manufacturing cell formation” , 2017 , The 19th International Conference on Soft Computing and Applications (ICSCA 2017) , 2017 /8 /17 ~ 2017 /8 /18 , Portuguese Republic .
  13. Y. Nataliani; M.S. Yang , “Spectral clustering for cell formation with minimum dissimilarities distance” , 2017 , The 2017 International Conference on Artificial Intelligence and Soft Computing (ICAISC 2017) , 2017 /6 /11 ~ 2017 /6 /15 , Republic of Poland .
  14. M.S. Yang , “A similarity-based clustering method for data on the unit hypersphere” , 2016 , The 9th European Computing Conference (ECC'16) (Invited plenary speaker) , 2016 /12 /17 ~ 2016 /12 /19 , Switzerland .
  15. M.S. Yang; R.J. Wong , “A learning-based EM algorithm for t-distribution mixtures” , 2016 , 2016 Global Conference on Engineering and Applied Science (GCEAS 2016) , 2016 /7 /19 ~ 2016 /7 /21 , Japan .
  16. W. Weku; M.S. Yang , “Robust GK fuzzy clustering algorithms with cluster core and analysis on parameter selection” , 2016 , The 2016 Asian Mathematical Conference (AMC 2016) , 2016 /7 /25 ~ 2016 /7 /29 , Republic of Indonesia .
  17. M.S. Yang , “Applications of fuzzy clustering in regression models” , 2016 , The 6th China Conference on Data Mining (CCDM 2016) (Invited speaker) , 2016 /5 /20 ~ 2016 /5 /22 , 大陸地區 .
  18. M.S. Yang , “On fuzzy change-point algorithms for regression models” , 2015 , Proceedings of the 20th International Conference on Applied Mathematics (AMATH'15) (Invited plenary speaker) , 2015 /12 /12 ~ 2015 /12 /14 , Hungary .
  19. Y.C. Tian; M.S. Yang , “A learning-based EM algorithm for mixture regression models” , 2015 , The 17th International Conference on Modelling, Optimization and Simulation (ICMOS 2015) , 2015 /7 /9 ~ 2015 /7 /10 , Czech Republic .
  20. M.S. Yang , “On maximum likelihood clustering via multimodal probability model” , 2014 , The 8th International Conference on Applied Mathematics, Simulation, Modelling (ASM’14) (Invited plenary speaker) , 2014 /11 /22 ~ 2014 /11 /24 , Italian Republic .
  21. M.S. Yang; C.Y. Lin; Y.C. Tian , “Fuzzy classification maximum likelihood clustering with t-distributions” , 2014 , The 4th International Conference on Mechanics, Simulation and Control (ICMSC2014) (Selected as the best oral presentation of the conference) , 2014 /6 /20 ~ 2014 /6 /23 , Russia .
  22. M.S. Yang , “Exponential-type robust clustering and its applications to interval data” , 2014 , 2014 Workshop in Symbolic Data Analysis (SDA 2014) (Invited speaker) , 2014 /6 /14 ~ 2014 /6 /16 , 中華民國 台灣 .
  23. M.S. Yang; W.L. Hung; S.J. Chang-Chien , “A robust clustering algorithm for directional data” , 2014 , International Conference Data Mining, Civil and Mechanical Engineering (ICDMCME’2014) , 2014 /2 /4 ~ 2014 /2 /5 , Republic of Indonesia .
  24. M.S. Yang , “Cluster-wise regression analysis using fuzzy set theory” , 2013 , Proceedings of 2013 NIMS Hot Topics Workshops on Prediction Using Fuzzy Theory (Invited speaker) , 2013 /8 /12 ~ 2013 /8 /14 , Republic of Korea .
  25. M.S. Yang; Y.S. Pan , “Sample-weighted fuzzy clustering with regularizations” , 2013 , Proceedings of 2013 International Conference on Machine Vision, Image Processing, and Pattern Analysis (ICMVIPPA-2013) , 2013 /7 /15 ~ 2013 /7 /16 , Sweden .
  26. M.S. Yang , “On robust expectation & maximization clustering algorithm” , 2013 , Proceedings of the 12th International Conference on Applied Computer and Applied Computational Science (Invited plenary speaker) , 2013 /4 /2 ~ 2013 /4 /4 , Malaysia .
  27. M.S. Yang; W.Q. Lin , “A weighted correlation coefficient control chart pattern recognition system” , 2012 , IEEE Proceedings of 2012 International Conference on Mechanic Automation and Control Engineering , 2012 /7 /27 ~ 2012 /7 /29 , 大陸地區 .
  28. M.S. Yang; H.C. Kuo; W.L. Hung , “A robust clustering algorithm for interval data” , 2012 , Proceedings of WCCI 2012 IEEE World Congress on Computational Intelligence, FUZZ-IEEE 2012 , 2012 /6 /10 ~ 2012 /6 /15 , Australia .
  29. M.S. Yang , “On robust possibilistic c-means clustering algorithm” , 2012 , Proceedings of the 11th WSEAS International Conference on Applied Computer and Applied Computational Science (Invited plenary speaker) , 2012 /4 /18 ~ 2012 /4 /20 , Republic of Finland .
  30. C.N. Wang; M.S. Yang , “T-transitive interval-valued fuzzy relations for clustering” , 2012 , IEEE Proceedings of 2012 International Conference on Computer Distributed Control and Intelligent Enviromental Monitoring , 2012 /3 /5 ~ 2012 /3 /6 , 大陸地區 .
  31. K.L. Wu; M.S. Yang , “On the generalized fuzzy-valued measures ” , 2011 , IEEE Proceedings of 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) , 2011 /7 /26 ~ 2011 /7 /28 , 大陸地區 .
  32. W.L. Hung; M.S. Yang; C.M. Hwang , “Exponential-Distance Weighted K-Means Algorithm with Spatial Constraints for Color Image Segmentation” , 2011 , IEEE Proceedings of 2011 International Conference on Multimedia and Signal Processing , 2011 /5 /13 ~ 2011 /5 /15 , 大陸地區 .
  33. C.M. Hwang; M.S. Yang; W.L. Hung , “New similarity and inclusion measures between type-2 fuzzy sets” , 2011 , Proceedings of IEEE Symposium Series on Computational Intelligence, IEEE-SSCI2011 on T2FUZZ-2011 , 2011 /4 /11 ~ 2011 /4 /15 , France .
  34. C.M. Hwang; W.L. Hung; M.S. Yang , “Adaptive weighted k-means algorithm for color image segmentation” , 2011 , Proceedings of the 2011 3rd International Conference on Computer Modeling and Simulation , 2011 /1 /7 ~ 2011 /1 /9 , Republic of India .
  35. S.J. Chang-Chien; M.S. Yang; W.L. Hung , “Mean shift-based clustering for directional data” , 2010 , IEEE Proceedings of Third International Workshop on Advanced Computational Intelligence , 2010 /8 /25 ~ 2010 /8 /27 , 大陸地區 .
  36. D.H. Chen; W.L. Hung; M.S. Yang , “A batch version of the SOM for symbolic data” , 2010 , IEEE Proceedings of the 2010 Sixth International Conference on Natural Computation , 2010 /8 /10 ~ 2010 /8 /12 , 大陸地區 .
  37. M.S. Yang , “On robust fuzzy clustering and validity indexes” , 2010 , Proceedings of the 11th WSEAS International Conference on Fuzzy Systems, In: Recent Advances in Neural Networks, Fuzzy Systems & Evolutionary Computing. (Invited plenary speaker) , 2010 /6 /13 ~ 2010 /6 /15 , Romania .
  38. M.S. Yang; J.H Yang; C.Y. Lai , “An integrated control chart pattern recognition system using correlation coefficient method and RBF neural networks” , 2010 , Proceedings of the Sixth IASTED International Conference on Advances in Computer Science and Engineering (ACSE 2010) , 2010 /3 /15 ~ 2010 /3 /17 , Arab Republic of Egypt .
  39. D.H. Chen; M.S. Yang; W.L. Hung , “A modified SOM learning algorithm for mixed types of symbolic and fuzzy data” , 2009 , Proceedings of 2009 WSEAS International Conference on Mathematical Methods and Applied Computing , 2009 /9 /28 ~ 2009 /9 /30 , Hellenic Republic .
  40. W.L. Hung; M.S. Yang; D.H. Chen , “Segmentation in MRI of ophthalmology using a robust-type clustering algorithms” , 2009 , Proceedings of the 2009 IEEE International Conference on Fuzzy Systems , 2009 /8 /20 ~ 2009 /8 /24 , Republic of Korea .
  41. M.S. Yang; Chih-Ying Lin , “Block fuzzy k-modes clustering algorithm” , 2009 , Proceedings of the 2009 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2009 , 2009 /8 /20 ~ 2009 /8 /24 , Republic of Korea .
  42. M.S. Yang; J.H. Yang , “On parameter estimation of control chart patterns using RBF neural network” , 2009 , Proceedings of the 4th IEEE Conference on Industrial Electronics and Applications , 2009 /5 /25 ~ 2009 /5 /27 , 大陸地區 .
  43. K.L. Wu; M.S. Yang; J.N. Hsieh , “Alternative fuzzy switching regression” , 2009 , Proceedings of International Multi-Conference of Engineers and Computer Scientists 2009 , 2009 /3 /18 ~ 2009 /3 /20 , 大陸地區 .
  44. W.L. Hung; M.S. Yang; D.H. Chen , “Variation approaches to feature-weight selection and application to fuzzy clustering” , 2008 , 2008 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2008 , 2008 /6 /1 ~ 2008 /6 /6 , 大陸地區 .
  45. M.S. Yang; K.C.R. Lin; H.C. Liu; J.F. Lirng , “A fuzzy-soft competitive learning algorithm for ophthalmological MRI segmentation” , 2008 , Proceedings of the 2008 WSEAS International Conference on Applied Computing , 2008 /5 /27 ~ 2008 /5 /30 , Republic of Turkey .
  46. M.S. Yang; J.H. Yang , “Control chart pattern recognition using semi-supervised learning” , 2007 , 7th WSEAS International Conference on Applied Computer Science , 2007 /11 /21 ~ 2007 /11 /23 , Italian Republic .
  47. W.L. Hung; M.S. Yang; D.H. Chen , “Color image segmentation using Cauchy-type fuzzy c-means algorithm” , 2007 , Proceedings of the 4th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD-2007 , 2007 /8 /24 ~ 2007 /8 /27 , 大陸地區 .
  48. M.S. Yang; K.L. Wu; J.N. Hsieh , “Mountain c-regressions in comparing fuzzy c-regressions” , 2007 , Proceedings of 2007 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2007 , 2007 /7 /23 ~ 2007 /7 /26 , United Kingdom .
  49. M.S. Yang, W.L. Hung, C.H. Chang , “A penalized fuzzy clustering algorithm” , 2006 , 6th WSEAS International Conference on Applied Computer Science , 2006 /12 /16 ~ 2006 /12 /18 , Spain .
  50. M.S. Yang; W.L. Hung; T.I. Chung , “Alternative fuzzy c-means clustering algorithms with L1-norm and covariance matrix” , 2006 , The 8th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2006 , 2006 /9 /18 ~ 2006 /9 /21 , Belgium .
  51. M.S. Yang and H.S. Tsai , “An alternative fuzzy compactness and separation clustering algorithm” , 2005 , Proceedings of the 7th International Conference on Advanced Concepts for Intelligent Vision Systems , 2005 /9 /5 ~ 2005 /9 /8 , Belgium .
  52. M.S. Yang and K.L. Wu , “An unsupervised alternating clustering method” , 2004 , 2nd IASTED International Conference on Neural Networks and Computational Intelligence , 2004 /12 /15 ~ 2004 /12 /17 , Switzerland .
  53. M.S. Yang, K.L. Wu and J. Yu , “A novel fuzzy clustering algorithm” , 2003 , 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation , 2003 /7 /5 ~ 2003 /7 /7 , Japan .
  54. M.S. Yang and K. L. Wu , “A possibilistic type of alternative fuzzy c-means” , 2002 , 2002 IEEE International Conference on Fuzzy Systems , 2002 /5 /12 ~ 2002 /5 /15 , United States .
  55. Y.Y. Hong, C.N. Chang-Chien, K.L. Wu and M.S. Yang , “Determination of congestion zones in deregulated electricity markets using fuzzy clustering” , 2002 , 14th power Systems Computation Conference , 2002 /5 /11 ~ 2002 /5 /13 , Spain .
  56. M.S.Yang and K.L. Wu , “A new validity index for fuzzy clustering” , 2001 , 10th IEEE International Conference on Fuzzy Systems , 2001 /11 /7 ~ 2001 /11 /10 , Australia .
  57. M.S.Yang and H.M. Chen , “Logistic regression analysis with fuzzy clustering algorithm” , 2001 , 中華民國第九屆模糊理論與應用研討會 , 2001 /4 /16 ~ 2001 /3 /18 , 中華民國 台灣 .
  58. C.C. Hung, M.S. Yang, S.Y. Shin and T.L. Coleman , “Evolution, fuzzy logic, and neural networks in unsupervised training algorithms” , 2000 , International Association for Computer and Information Science 1st International Conference , 2000 ~ 2000 .
  59. M.S. Yang , “On Classification regression analysis With a Noise Cluster” , 1997 , 中華民國第五屆模糊理論與應用研討會 , 2002 ~ 2002 .
專書
  1. 楊敏生; 楊鎮槐 , “模糊聚類及其應用” , 藍海文化出版 , 2009 .
技術報告
  1. 楊敏生, 劉曼君 , “可能性理論簡介” , 1996 .
  2. 楊敏生 , “模糊理論簡介” , 1994 .