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ORCIDSadaaki Miyamoto
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- affiliation: University of Tsukuba, Japan
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2020 – today
- 2022
[j74]Yuchi Kanzawa, Sadaaki Miyamoto:
Generalization of Tsallis Entropy-Based Fuzzy c-Means Clustering and its Behavior at the Infinity Point. J. Adv. Comput. Intell. Intell. Informatics 26(6): 884-892 (2022)- 2021
- [j73]Yuchi Kanzawa, Sadaaki Miyamoto:
Generalized Fuzzy c-Means Clustering and its Property of Fuzzy Classification Function. J. Adv. Comput. Intell. Intell. Informatics 25(1): 73-82 (2021)
2010 – 2019
- 2019
- [j72]Yuchi Kanzawa, Sadaaki Miyamoto:
Regularized Fuzzy c-Means Clustering and its Behavior at Point of Infinity. J. Adv. Comput. Intell. Intell. Informatics 23(3): 485-492 (2019) - 2018
- [j71]Sadaaki Miyamoto:
Editorial: Recent Methodological Developments in Fuzzy Clustering and Related Topics. J. Adv. Comput. Intell. Intell. Informatics 22(4): 523 (2018) - [c132]Sadaaki Miyamoto, Van-Nam Huynh, Shuhei Fujiwara:
Methods for Clustering Categorical and Mixed Data: An Overview and New Algorithms. IUKM 2018: 75-86 - [c131]Sadaaki Miyamoto, Jong Moon Choi, Yasunori Endo, Van-Nam Huynh:
Optimal Clustering with Twofold Memberships. MDAI 2018: 221-231 - [c130]Yuchi Kanzawa, Sadaaki Miyamoto:
Generalized Fuzzy c-Means Clustering and Its Theoretical Properties. MDAI 2018: 243-254 - 2017
- [c129]Sadaaki Miyamoto:
Contributions of Fuzzy Concepts to Data Clustering. Fuzzy Sets, Rough Sets, Multisets and Clustering 2017: 9-28 - [c128]Ryosuke Abe, Sadaaki Miyamoto, Yasunori Endo, Yukihiro Hamasuna:
Hierarchical clustering algorithms with automatic estimation of the number of clusters. IFSA-SCIS 2017: 1-5 - 2016
- [j70]Tatsuya Higuchi, Sadaaki Miyamoto, Yasunori Endo:
Fuzzy c-Regression Models for Fuzzy Numbers on a Graph. J. Adv. Comput. Intell. Intell. Informatics 20(4): 521-534 (2016) - [c127]Sadaaki Miyamoto, Yoshiyuki Komazaki, Yasunori Endo:
Generalizations of Fuzzy c-Means and Fuzzy Classifiers. IUKM 2016: 151-162 - [c126]Sadaaki Miyamoto, Yousuke Kaizu, Yasunori Endo:
Hierarchical and Non-Hierarchical Medoid Clustering Using Asymmetric Similarity Measures. SCIS&ISIS 2016: 400-403 - [c125]Tsubasa Hirano, Yasunori Endo, Naohiko Kinoshita, Sadaaki Miyamoto:
A Note on Even-Sized Clustering Based on Optimization. SCIS&ISIS 2016: 404-409 - 2015
- [j69]Tetsuya Murai, Sadaaki Miyamoto, Masahiro Inuiguchi, Yasuo Kudo
, Seiki Akama:
Fuzzy Multisets in Granular Hierarchical Structures Generated from Free Monoids. J. Adv. Comput. Intell. Intell. Informatics 19(1): 43-50 (2015) - [j68]Hengjin Tang, Sadaaki Miyamoto, Yasunori Endo:
Semi-Supervised Sequential Kernel Regression Models with Penalty Functions. J. Adv. Comput. Intell. Intell. Informatics 19(1): 51-57 (2015) - [c124]Yousuke Kaizu, Sadaaki Miyamoto, Yasunori Endo:
Hard and Fuzzy c-Medoids for Asymmetric Networks. IFSA-EUSFLAT 2015 - [c123]Yasunori Endo, Tomoyuki Suzuki, Naohiko Kinoshita, Yukihiro Hamasuna, Sadaaki Miyamoto:
Fuzzy non-metric model for data with tolerance and its application to incomplete data clustering. FUZZ-IEEE 2015: 1-7 - [c122]Sadaaki Miyamoto:
Fuzzy Sets, Multisets, and Rough Approximations. IUKM 2015: 11-14 - [c121]Yasunori Endo, Sadaaki Miyamoto:
Spherical k-Means++ Clustering. MDAI 2015: 103-114 - [c120]Sadaaki Miyamoto, Ryosuke Abe, Yasunori Endo, Jun-ichi Takeshita:
Ward method of hierarchical clustering for non-Euclidean similarity measures. SoCPaR 2015: 60-63 - [p1]Sadaaki Miyamoto:
Fuzzy Clustering - Basic Ideas and Overview. Handbook of Computational Intelligence 2015: 239-248 - 2014
- [j67]Sadaaki Miyamoto:
Classification Rules in Methods of Clustering. IEEE Intell. Informatics Bull. 15(1): 15-21 (2014) - [j66]Tetsuya Murai, Sadaaki Miyamoto, Masahiro Inuiguchi, Yasuo Kudo, Seiki Akama:
Crisp and Fuzzy Granular Hierarchical Structures Generated from a Free Monoid. J. Adv. Comput. Intell. Intell. Informatics 18(6): 929-936 (2014) - [c119]Tatsuya Higuchi, Sadaaki Miyamoto:
Fuzzy c-regression models combined with support vector regression. FUZZ-IEEE 2014: 2489-2493 - [c118]Zhang Canlun, Sadaaki Miyamoto:
Text clustering using fuzzy neighborhood and evaluation of clusters. GrC 2014: 19-24 - [c117]So Miyahara, Sadaaki Miyamoto:
A family of algorithms using spectral clustering and DBSCAN. GrC 2014: 196-200 - [c116]Yusuke Tamura, Sadaaki Miyamoto:
A method of two stage clustering using agglomerative hierarchical algorithms with one-pass k-means++ or k-median++. GrC 2014: 281-285 - [c115]Yusuke Tamura, Sadaaki Miyamoto:
Two-stage clustering using one-pass K-medoids and medoid-based agglomerative hierarchical algorithms. SCIS&ISIS 2014: 484-488 - [c114]Naohiko Kinoshita, Yasunori Endo, Sadaaki Miyamoto:
On Some Models of Objective-Based Rough Clustering. WI-IAT (1) 2014: 392-399 - 2013
- [j65]Tsau-Young Lin, Yasuo Kudo, Sadaaki Miyamoto:
Introduction to Special Issue on "Foundations and Applications of Granular Computing". Int. J. Intell. Syst. 28(9): 841-842 (2013) - [j64]Satoshi Takumi, Sadaaki Miyamoto:
Nearest Prototype and Nearest Neighbor Clustering with Twofold Memberships Based on Inductive Property. J. Adv. Comput. Intell. Intell. Informatics 17(4): 504-510 (2013) - [c113]Sadaaki Miyamoto, Nobuhiro Obara:
Algorithms of crisp, fuzzy, and probabilistic clustering with semi-supervision or pairwise constraints. GrC 2013: 225-230 - [c112]Hengjin Tang, Sadaaki Miyamoto:
Sequential extraction of clusters for imbalanced data. GrC 2013: 281-285 - [c111]Yusuke Tamura, Nobuhiro Obara, Sadaaki Miyamoto:
A Method of Two-Stage Clustering with Constraints Using Agglomerative Hierarchical Algorithm and One-Pass k-Means++. KSE (2) 2013: 9-19 - [c110]So Miyahara, Yoshiyuki Komazaki, Sadaaki Miyamoto:
An Algorithm Combining Spectral Clustering and DBSCAN for Core Points. KSE (2) 2013: 21-28 - [c109]Hengjin Tang, Sadaaki Miyamoto:
Semi-supervised Sequential Kernel Regression Models with Pairwise Constraints. MDAI 2013: 166-178 - [c108]Yoshiyuki Komazaki, Sadaaki Miyamoto:
Variables for Controlling Cluster Sizes on Fuzzy c-Means. MDAI 2013: 192-203 - [c107]Tetsuya Murai, Sadaaki Miyamoto, Masahiro Inuiguchi, Yasuo Kudo, Seiki Akama:
Fuzzy Multisets in Granular Hierarchical Structures Generated from Free Monoids. MDAI 2013: 248-259 - 2012
- [j63]Sadaaki Miyamoto:
Different generalizations of bags. Ann. Oper. Res. 195(1): 221-236 (2012) - [j62]Tetsuya Murai, Sadaaki Miyamoto, Masahiro Inuiguchi, Seiki Akama:
Granular hierarchical structures of finite naïve subsets and multisets based on free monoids and homomorphisms. Int. J. Reason. based Intell. Syst. 4(3): 118-128 (2012) - [j61]Van-Nam Huynh, Sadaaki Miyamoto, Yoshiteru Nakamori:
An extension of context model for representing vague knowledge. Int. J. Reason. based Intell. Syst. 4(3): 171-179 (2012) - [j60]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
On Kernel Fuzzy c-Means for Data with Tolerance Using Explicit Mapping for Kernel Data Analysis. J. Adv. Comput. Intell. Intell. Informatics 16(1): 162-168 (2012) - [j59]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
On Agglomerative Hierarchical Clustering Using Clusterwise Tolerance Based Pairwise Constraints. J. Adv. Comput. Intell. Intell. Informatics 16(1): 174-179 (2012) - [j58]Satoshi Takumi, Sadaaki Miyamoto:
Agglomerative Hierarchical Clustering Without Reversals on Dendrograms Using Asymmetric Similarity Measures. J. Adv. Comput. Intell. Intell. Informatics 16(7): 807-813 (2012) - [j57]Hengjin Tang, Sadaaki Miyamoto:
Sequential Regression Models with Pairwise Constraints Using Noise Clusters. J. Adv. Comput. Intell. Intell. Informatics 16(7): 814-818 (2012) - [j56]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Hard and Fuzzy c-Means Clustering with Conditionally Positive Definite Kernel. J. Adv. Comput. Intell. Intell. Informatics 16(7): 825-830 (2012) - [c106]Sadaaki Miyamoto, Shohei Suzuki, Satoshi Takumi:
Clustering in tweets using a fuzzy neighborhood model. FUZZ-IEEE 2012: 1-6 - [c105]Sadaaki Miyamoto:
Inductive and non-inductive methods of clustering. GrC 2012: 12-17 - [c104]Sadaaki Miyamoto, Satoshi Takumi:
Hierarchical clustering using transitive closure and semi-supervised classification based on fuzzy rough approximation. GrC 2012: 359-364 - [c103]Satoshi Takumi, Sadaaki Miyamoto:
Top-down vs bottom-up methods of linkage for asymmetric agglomerative hierarchical clustering. GrC 2012: 459-464 - [c102]Sadaaki Miyamoto:
An Overview of Hierarchical and Non-hierarchical Algorithms of Clustering for Semi-supervised Classification. MDAI 2012: 1-10 - [c101]Sadaaki Miyamoto, Satoshi Takumi:
Inductive Clustering and Twofold Approximations in Nearest Neighbor Clustering. MDAI 2012: 355-366 - [c100]Nobuhiro Obara, Sadaaki Miyamoto:
A method of two-stage clustering with constraints using agglomerative hierarchical algorithm and one-pass k-means. SCIS&ISIS 2012: 1540-1544 - [c99]Satoshi Takumi, Sadaaki Miyamoto:
Comparing different methods of agglomerative hierarchical clustering with pairwise constraints. SCIS&ISIS 2012: 1545-1550 - [c98]Ayako Heki, Yasunori Endo, Sadaaki Miyamoto:
Rough set based non metric model. SCIS&ISIS 2012: 1778-1783 - 2011
- [j55]Vicenç Torra, Yasunori Endo, Sadaaki Miyamoto:
Computationally intensive parameter selection for clustering algorithms: The case of fuzzy c-means with tolerance. Int. J. Intell. Syst. 26(4): 313-322 (2011) - [j54]Hengjin Tang, Sadaaki Miyamoto:
Sequential Extraction of Fuzzy Regression Models: Least Squares and Least absolute Deviations. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 19(Supplement-1): 53-63 (2011) - [j53]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy c-Means Clustering for Data with Clusterwise Tolerance Based on L2- and L1-Regularization. J. Adv. Comput. Intell. Intell. Informatics 15(1): 68-75 (2011) - [j52]Jeongsik Hwang, Sadaaki Miyamoto:
Kernel Functions Derived from Fuzzy Clustering and Their Application to Kernel Fuzzy c-Means. J. Adv. Comput. Intell. Intell. Informatics 15(1): 90-94 (2011) - [j51]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Semi-Supervised Fuzzy c-Means Algorithm by Revising Dissimilarity Between Data. J. Adv. Comput. Intell. Intell. Informatics 15(1): 95-101 (2011) - [j50]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
KL-Divergence-Based and Manhattan Distance-Based Semisupervised Entropy-Regularized Fuzzy c-Means. J. Adv. Comput. Intell. Intell. Informatics 15(8): 1057-1064 (2011) - [j49]Vicenç Torra, Sadaaki Miyamoto:
A definition for I-fuzzy partitions. Soft Comput. 15(2): 363-369 (2011) - [j48]Vicenç Torra, Sadaaki Miyamoto:
Erratum to: A definition for I-fuzzy partitions. Soft Comput. 15(2): 371 (2011) - [c97]Sadaaki Miyamoto, Keisuke Sawazaki:
A method of explicit mappings for kernel data analysis and applications. FUZZ-IEEE 2011: 381-385 - [c96]Sadaaki Miyamoto, Akihisa Terami:
Constrained agglomerative hierarchical clustering algorithms with penalties. FUZZ-IEEE 2011: 422-427 - [c95]Yasunori Endo, Isao Takayama, Yukihiro Hamasuna, Sadaaki Miyamoto:
Kernelized fuzzy c-means clustering for uncertain data using quadratic penalty-vector regularization with explicit mappings. FUZZ-IEEE 2011: 804-809 - [c94]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
On Mahalanobis distance based fuzzy c-means clustering for uncertain data using penalty vector regularization. FUZZ-IEEE 2011: 810-815 - [c93]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
On hard and fuzzy c-means clustering with conditionally positive definite kernel. FUZZ-IEEE 2011: 816-820 - [c92]Aoi Takahashi, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy c-means clustering for data with tolerance using cosine correlation. GrC 2011: 619-624 - [c91]Satoshi Takumi, Sadaaki Miyamoto:
Text clustering using a multiset model. GrC 2011: 630-635 - [c90]Sadaaki Miyamoto, Akihisa Terami:
Inductive vs. transductive clustering using kernel functions and pairwise constraints. ISDA 2011: 1258-1264 - [c89]Sadaaki Miyamoto:
Two Classes of Algorithms for Data Clustering. IUKM 2011: 19-30 - [c88]Satoshi Takumi, Sadaaki Miyamoto:
Agglomerative Hierarchical Clustering Using Asymmetric Similarity Based on a Bag Model and Application to Information on the Web. IUKM 2011: 187-196 - [c87]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Semi-supervised Agglomerative Hierarchical Clustering with Ward Method Using Clusterwise Tolerance. MDAI 2011: 103-113 - [c86]Satoshi Takumi, Sadaaki Miyamoto:
Agglomerative Clustering Using Asymmetric Similarities. MDAI 2011: 114-125 - 2010
- [j47]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
On tolerant fuzzy c-means clustering and tolerant possibilistic clustering. Soft Comput. 14(5): 487-494 (2010) - [j46]Vicenç Torra, Isaac Cano, Sadaaki Miyamoto, Yasunori Endo:
Container loading for nonorthogonal objects: an approximation using local search and simulated annealing. Soft Comput. 14(5): 537-544 (2010) - [c85]Yasunori Endo, Kouta Kurihara, Sadaaki Miyamoto, Yukihiro Hamasuna:
Hard and fuzzy c-regression models for data with tolerance in independent and dependent variables. FUZZ-IEEE 2010: 1-8 - [c84]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Cluster validity measures for data with tolerance. FUZZ-IEEE 2010: 1-6 - [c83]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
On kernel fuzzy c-means for data with tolerance using explicit mapping for kernel data analysis. FUZZ-IEEE 2010: 1-6 - [c82]Sadaaki Miyamoto, Akihisa Terami:
Semi-supervised agglomerative hierarchical clustering algorithms with pairwise constraints. FUZZ-IEEE 2010: 1-6 - [c81]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Semi-supervised Fuzzy c-Means Clustering Using Clusterwise Tolerance Based Pairwise Constraints. GrC 2010: 188-193 - [c80]Sadaaki Miyamoto:
Bags, Toll Sets, and Fuzzy Sets. IUM 2010: 307-317 - [c79]Tetsuya Murai, Seiki Ubukata, Yasuo Kudo, Seiki Akama, Sadaaki Miyamoto:
Granularity and Approximation in Sequences, Multisets, and Sets in the Framework of Kripke Semantics. IUM 2010: 329-334 - [c78]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Indefinite Kernel Fuzzy c-Means Clustering Algorithms. MDAI 2010: 116-128 - [c77]Hengjin Tang, Sadaaki Miyamoto:
Algorithms in Sequential Fuzzy Regression Models Based on Least Absolute Deviations. MDAI 2010: 129-139 - [c76]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Semi-supervised Agglomerative Hierarchical Clustering Using Clusterwise Tolerance Based Pairwise Constraints. MDAI 2010: 152-162
2000 – 2009
- 2009
- [j45]Wataru Hashimoto, Tetsuya Nakamura, Sadaaki Miyamoto:
Comparison and Evaluation of Different Cluster Validity Measures Including Their Kernelization. J. Adv. Comput. Intell. Intell. Informatics 13(3): 204-209 (2009) - [j44]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
On Tolerant Fuzzy c -Means Clustering. J. Adv. Comput. Intell. Intell. Informatics 13(4): 421-428 (2009) - [j43]Vicenç Torra, Yasunori Endo, Sadaaki Miyamoto:
On the Comparison of Some Fuzzy Clustering Methods for Privacy Preserving Data Mining: Towards the Development of Specific Information Loss Measures. Kybernetika 45(3): 548-560 (2009) - [c75]Sadaaki Miyamoto:
Operations for Real-Valued Bags and Bag Relations. IFSA/EUSFLAT Conf. 2009: 612-617 - [c74]Sadaaki Miyamoto, Yuichi Kawasaki, Keisuke Sawazaki:
An Explicit Mapping for Kernel Data Analysis and Application to Text Analysis. IFSA/EUSFLAT Conf. 2009: 618-623 - [c73]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy c-Lines for Data with Tolerance. IFSA/EUSFLAT Conf. 2009: 861-866 - [c72]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
On Tolerant Fuzzy c-Means Clustering with L1-Regularization. IFSA/EUSFLAT Conf. 2009: 1152-1157 - [c71]Sadaaki Miyamoto, Kenta Arai:
Different sequential clustering algorithms and sequential regression models. FUZZ-IEEE 2009: 1107-1112 - [c70]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Entropy regularized fuzzy C-lines for data with tolerance. FUZZ-IEEE 2009: 1113-1118 - [c69]Yasunori Endo, Yukihiro Hamasuna, Makito Yamashiro, Sadaaki Miyamoto:
On semi-supervised fuzzy c-means clustering. FUZZ-IEEE 2009: 1119-1124 - [c68]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
On L1-Norm based tolerant fuzzy c-Means clustering. FUZZ-IEEE 2009: 1125-1130 - [c67]Sadaaki Miyamoto:
Generalized bags and their relations: An alternative model for fuzzy set theory and applications. GrC 2009: 3 - [c66]Yasunori Endo, Yukihiro Hamasuna, Yuchi Kanzawa, Sadaaki Miyamoto:
On fuzzy c-means clustering for uncertain data using quadratic regularization of penalty vectors. GrC 2009: 148-153 - [c65]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Comparison of tolerant fuzzy c-means clustering with L2- and L1-regularization. GrC 2009: 197-202 - [c64]Yasuo Kudo, Tetsuya Murai, Sadaaki Miyamoto:
On an extraction method of structural characteristics in object-oriented rough set models. GrC 2009: 312-317 - [c63]Sadaaki Miyamoto, Mitsuaki Yamazaki, Wataru Hashimoto:
Fuzzy semi-supervised clustering with target clusters using different additional terms. GrC 2009: 444-449 - [c62]Sadaaki Miyamoto:
Generalized Bags, Bag Relations, and Applications to Data Analysis and Decision Making. MDAI 2009: 37-54 - [c61]Sadaaki Miyamoto:
Refinement Properties in Agglomerative Hierarchical Clustering. MDAI 2009: 259-267 - [c60]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Some Pairwise Constrained Semi-Supervised Fuzzy c-Means Clustering Algorithms. MDAI 2009: 268-281 - 2008
- [b1]Sadaaki Miyamoto, Hidetomo Ichihashi, Katsuhiro Honda:
Algorithms for Fuzzy Clustering - Methods in c-Means Clustering with Applications. Studies in Fuzziness and Soft Computing 229, Springer 2008, ISBN 978-3-540-78736-5, pp. 1-233 [contents] - [j42]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy c-Means Algorithms for Data with Tolerance Using Kernel Functions. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 91-A(9): 2520-2534 (2008) - [j41]Kiyotaka Mizutani, Ryo Inokuchi, Sadaaki Miyamoto:
Algorithms of nonlinear document clustering based on fuzzy multiset model. Int. J. Intell. Syst. 23(2): 176-198 (2008) - [j40]Vicenç Torra, Sadaaki Miyamoto:
Container Loading for Nonorthogonal Objects: Detecting Collisions. J. Adv. Comput. Intell. Intell. Informatics 12(5): 422-425 (2008) - [j39]Ryo Inokuchi, Sadaaki Miyamoto:
Fuzzy c-Means Algorithms Using Kullback-Leibler Divergence and Helliger Distance Based on Multinomial Manifold. J. Adv. Comput. Intell. Intell. Informatics 12(5): 443-447 (2008) - [j38]Sadaaki Miyamoto, Youhei Kuroda, Kenta Arai:
Algorithms for Sequential Extraction of Clusters by Possibilistic Method and Comparison with Mountain Clustering. J. Adv. Comput. Intell. Intell. Informatics 12(5): 448-453 (2008) - [j37]Sadaaki Miyamoto:
Formulation of Fuzzy c-Means Clustering Using Calculus of Variations and Twofold Membership Clusters. J. Adv. Comput. Intell. Intell. Informatics 12(5): 454-460 (2008) - [j36]Yasunori Endo, Yasushi Hasegawa, Yukihiro Hamasuna, Sadaaki Miyamoto:
Fuzzy c-Means for Data with Rectangular Maximum Tolerance Range. J. Adv. Comput. Intell. Intell. Informatics 12(5): 461-466 (2008) - [c59]Sadaaki Miyamoto:
Generalized Bags and Bag Relations: Toward an Alternative Model for Fuzzy Set Applications. CIMCA/IAWTIC/ISE 2008: 380-385 - [c58]Sadaaki Miyamoto, Yuichi Kawasaki:
Kernel space for text analysis based on fuzzy neighborhoods. FUZZ-IEEE 2008: 738-743 - [c57]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Support Vector Machine for data with tolerance based on Hard-margin and Soft-Margin. FUZZ-IEEE 2008: 750-755 - [c56]Vicenç Torra, Sadaaki Miyamoto, Yasunori Endo, Josep Domingo-Ferrer:
On intuitionistic fuzzy clustering for its application to privacy. FUZZ-IEEE 2008: 1042-1048 - [c55]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy classification function of fuzzy c-means algorithms for data with tolerance. FUZZ-IEEE 2008: 1081-1088 - [c54]Sadaaki Miyamoto:
Recent Studies on Algorithms for Fuzzy Clustering. GrC 2008: 59-60 - [c53]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy Classification Function of Entropy Regularized Fuzzy C-means Algorithm for Data with Tolerance using Kernel Function. GrC 2008: 350-355 - [c52]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy Classification Function of Standard Fuzzy c-Means Algorithm for Data with Tolerance Using Kernel Function. MDAI 2008: 122-133 - [c51]Sadaaki Miyamoto:
Generalized Agglomerative Clustering with Application to Information Systems. MDAI 2008: 158-166 - 2007
- [j35]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy c-Means Algorithms for Data with Tolerance Based on Opposite Criterions. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 90-A(10): 2194-2202 (2007) - [j34]Vicenç Torra, Yasuo Narukawa, Sadaaki Miyamoto:
Editorial. J. Adv. Comput. Intell. Intell. Informatics 11(1): 3 (2007) - [j33]Sadaaki Miyamoto, Yasunori Endo, Koki Hanzawa, Yukihiro Hamasuna:
Metaheuristic Algorithms for Container Loading Problems: Framework and Knowledge Utilization. J. Adv. Comput. Intell. Intell. Informatics 11(1): 51-60 (2007) - [c50]Yukihiro Hamasuna, Yasunori Endo, Yasushi Hasegawa, Sadaaki Miyamoto:
Two Clustering Algorithms for Data with Tolerance based on Hard c-Means. FUZZ-IEEE 2007: 1-4 - [c49]Yasunori Endo, Yukihiro Hamasuna, Sadaaki Miyamoto:
Agglomerative Hierarchical Clustering for Data with Tolerance. GrC 2007: 404-409 - [c48]Ryo Inokuchi, Sadaaki Miyamoto:
Sparse Possibilistic Clustering with L1 Regularization. GrC 2007: 442- - [c47]Sadaaki Miyamoto, Satoshi Hayakawa, Yuichi Kawasaki:
Term Clustering in Texts Based on Fuzzy Neighborhoods and Kernel Functions. KES (2) 2007: 517-524 - [c46]Sadaaki Miyamoto:
Formulation of Fuzzy c -Means Clustering Using Calculus of Variations. MDAI 2007: 193-203 - [c45]Sadaaki Miyamoto, Youhei Kuroda:
Algorithms for Sequential Extraction of Clusters by Possibilistic Clustering. MDAI 2007: 226-236 - [c44]Yasushi Hasegawa, Yasunori Endo, Yukihiro Hamasuna, Sadaaki Miyamoto:
Fuzzy c -Means for Data with Tolerance Defined as Hyper-Rectangle. MDAI 2007: 237-248 - [c43]Sadaaki Miyamoto, Yuichi Kawasaki:
Kernel Functions Based on Fuzzy Neighborhoods and Agglomerative Clustering. MDAI 2007: 249-260 - [c42]Ryo Inokuchi, Sadaaki Miyamoto:
c -Means Clustering on the Multinomial Manifold. MDAI 2007: 261-268 - [c41]Sadaaki Miyamoto:
Data Clustering Algorithms for Information Systems. RSFDGrC 2007: 13-24 - [c40]Tetsuya Murai, Sadaaki Miyamoto, Yasuo Kudo:
A Logical Representation of Images by Means of Multi-rough Sets for Kansei Image Retrieval. RSKT 2007: 244-251 - 2006
- [j32]Vicenç Torra, Yasuo Narukawa, Sadaaki Miyamoto:
Editorial. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 14(4): 369-370 (2006) - [j31]Ryo Inokuchi, Sadaaki Miyamoto:
Kernel Methods for Clustering: Competitive Learning and C-Means. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 14(4): 481-493 (2006) - [j30]Sadaaki Miyamoto, Tetsuya Murai, Yasuo Kudo:
A Family of Polymodal Systems and its Application to Generalized Possibility Measures and Multi-Rough Sets. J. Adv. Comput. Intell. Intell. Informatics 10(5): 625-632 (2006) - [j29]Ryuichi Murata, Yasunori Endo, Hideyuki Haruyama, Sadaaki Miyamoto:
On Fuzzy c-Means for Data with Tolerance. J. Adv. Comput. Intell. Intell. Informatics 10(5): 673-681 (2006) - [j28]Vicenç Torra, Sergi Lanau, Sadaaki Miyamoto:
Image clustering for the exploration of video sequences. J. Assoc. Inf. Sci. Technol. 57(4): 577-584 (2006) - [c39]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy c-Means Clustering for Data with Tolerance Using Kernel Functions. FUZZ-IEEE 2006: 744-750 - [c38]Ryo Inokuchi, Tetsuya Nakamura, Sadaaki Miyamoto:
Kernelized Cluster Validity Measures and Application to Evaluation of Different Clustering Algorithms. FUZZ-IEEE 2006: 763-769 - [c37]Yasunori Endo, Ryuichi Murata, Hiromi Toyoda, Sadaaki Miyamoto:
L1-Norm based Fuzzy Clustering for Data with Tolerance. FUZZ-IEEE 2006: 770-777 - [c36]Sadaaki Miyamoto, Ryo Inokuchi, Youhei Kuroda:
Possibilistic and Fuzzy c-Means Clustering with Weighted Objects. FUZZ-IEEE 2006: 869-874 - [c35]Sadaaki Miyamoto:
Classification and Clustering: A Perspective toward Risk Mining. ICDM Workshops 2006: 726-730 - [c34]Ryo Inokuchi, Sadaaki Miyamoto:
Nonparametric Fisher Kernel Using Fuzzy Clustering. KES (2) 2006: 78-85 - [c33]Ryuichi Murata, Yasunori Endo, Hideyuki Haruyama, Sadaaki Miyamoto:
On Fuzzy c-Means for Data with Tolerance. MDAI 2006: 351-361 - [c32]Vicenç Torra, Sadaaki Miyamoto:
On the Use of Variable-Size Fuzzy Clustering for Classification. MDAI 2006: 362-371 - [c31]Sadaaki Miyamoto, Satoshi Hayakawa:
A Fuzzy Neighborhood Model for Clustering, Classification, and Approximations. RSCTC 2006: 882-890 - [c30]Sadaaki Miyamoto:
Lattice-Valued Hierarchical Clustering for Analyzing Information Systems. RSCTC 2006: 909-917 - [e2]Salvatore Greco, Yutaka Hata, Shoji Hirano, Masahiro Inuiguchi, Sadaaki Miyamoto, Hung Son Nguyen, Roman Slowinski:
Rough Sets and Current Trends in Computing, 5th International Conference, RSCTC 2006, Kobe, Japan, November 6-8, 2006, Proceedings. Lecture Notes in Computer Science 4259, Springer 2006, ISBN 3-540-47693-8 [contents] - 2005
- [j27]Sadaaki Miyamoto:
Remarks on basics of fuzzy sets and fuzzy multisets. Fuzzy Sets Syst. 156(3): 427-431 (2005) - [j26]Vicenç Torra, Sadaaki Miyamoto, Sergi Lanau:
Exploration of textual document archives using a fuzzy hierarchical clustering algorithm in the GAMBAL system. Inf. Process. Manag. 41(3): 587-598 (2005) - [c29]Vicenç Torra, Sadaaki Miyamoto:
On the consistency of a Fuzzy C-Means algorithm for multisets. CCIA 2005: 289-295 - [c28]Sadaaki Miyamoto, Takeshi Yasukochi, Ryo Inokuchi:
A Family of Fuzzy and Defuzzified c-Means Algorithms. CIMCA/IAWTIC 2005: 170-176 - [c27]Kiyotaka Mizutani, Sadaaki Miyamoto:
Kernel-Based Fuzzy Competitive Learning Clustering. FUZZ-IEEE 2005: 636-639 - [c26]Sadaaki Miyamoto, Erina Kataoka:
Algorithms for Clustering Terms in Document Set Based on Fuzzy Neighborhoods. FUZZ-IEEE 2005: 979-984 - [c25]Shigeyuki Takahara, Sadaaki Miyamoto:
An Evolutionary Approach for the Multiple Container Loading Problem. HIS 2005: 227-232 - [c24]Vicenç Torra, Yasuo Narukawa, Sadaaki Miyamoto:
Modeling Decisions for Artificial Intelligence: Theory, Tools and Applications. MDAI 2005: 1-8 - [c23]Kiyotaka Mizutani, Sadaaki Miyamoto:
Possibilistic Approach to Kernel-Based Fuzzy c-Means Clustering with Entropy Regularization. MDAI 2005: 144-155 - [c22]Arnold C. Alanzado, Sadaaki Miyamoto:
Fuzzy c-Means Clustering in the Presence of Noise Cluster for Time Series Analysis. MDAI 2005: 156-163 - [c21]Sadaaki Miyamoto, Yasunori Endo, Satoshi Hayakawa, Erina Kataoka:
Classification and clustering of information objects based on fuzzy neighborhood system. SMC 2005: 3210-3215 - [c20]Sadaaki Miyamoto, Takeshi Yasukochi, Ryo Inokuchi:
Defuzzified clustering algorithms derived from the method of entropy-based fuzzy c-means. SMC 2005: 3221-3225 - [e1]Vicenç Torra, Yasuo Narukawa, Sadaaki Miyamoto:
Modeling Decisions for Artificial Intelligence, Second International Conference, MDAI 2005, Tsukuba, Japan, July 25-27, 2005, Proceedings. Lecture Notes in Computer Science 3558, Springer 2005, ISBN 3-540-27871-0 [contents] - 2004
- [j25]Sadaaki Miyamoto:
Generalizations of multisets and rough approximations. Int. J. Intell. Syst. 19(7): 639-652 (2004) - [j24]Sadaaki Miyamoto:
Data Structure and Operations for Fuzzy Multisets. Trans. Rough Sets 2: 189-200 (2004) - [c19]Ryo Inokuchi, Sadaaki Miyamoto:
LVQ clustering and SOM using a kernel function. FUZZ-IEEE 2004: 1497-1500 - [c18]Sadaaki Miyamoto:
Multisets and Fuzzy Multisets as a Framework of Information Systems. MDAI 2004: 27-40 - [c17]Sadaaki Miyamoto, Kiyotaka Mizutani:
Fuzzy Multiset Model and Methods of Nonlinear Document Clustering for Information Retrieval. MDAI 2004: 273-283 - [c16]Vicenç Torra, Sadaaki Miyamoto:
Evaluating Fuzzy Clustering Algorithms for Microdata Protection. Privacy in Statistical Databases 2004: 175-186 - 2003
- [j23]Sadaaki Miyamoto:
Proximity measures for terms based on fuzzy neighborhoods in document sets. Int. J. Approx. Reason. 34(2-3): 181-199 (2003) - [j22]Sadaaki Miyamoto:
Information clustering based on fuzzy multisets. Inf. Process. Manag. 39(2): 195-213 (2003) - [j21]Sadaaki Miyamoto, Youichi Nakayama:
Algorithms of Hard c-Means Clustering Using Kernel Functions in Support Vector Machines. J. Adv. Comput. Intell. Intell. Informatics 7(1): 19-24 (2003) - [j20]Sadaaki Miyamoto, Daisuke Suizu:
Fuzzy c-Means Clustering Using Kernel Functions in Support Vector Machines. J. Adv. Comput. Intell. Intell. Informatics 7(1): 25-30 (2003) - [j19]Sadaaki Miyamoto, Seiji Yasunobu:
Editorial: Special Issue on Selected Papers from SCIS & ISIS 2002. J. Adv. Comput. Intell. Intell. Informatics 7(2): 71 (2003) - [j18]Zhi-Qiang Liu, Sadaaki Miyamoto:
Preface of the guest Editors. Soft Comput. 7(3): 139 (2003) - [j17]Shigeyuki Takahara, Yoshiyuki Kusumoto, Sadaaki Miyamoto:
Solution for textile nesting problems using adaptive meta-heuristics and grouping. Soft Comput. 7(3): 154-159 (2003) - [c15]Vicenç Torra, Sergi Lanau, Sadaaki Miyamoto:
Fuzzy clustering for indexing in the GAMBAL information retrieval system. EUSFLAT Conf. 2003: 54-58 - [c14]Sadaaki Miyamoto, Kiyotaka Mizutani:
Fuzzy Multiset Space and c-Means Clustering Using Kernles with Applications to Information Retrieval. IFSA 2003: 387-395 - [c13]Kiyotaka Mizutani, Sadaaki Miyamoto:
Fuzzy Multiset Model for Information Retrieval and Clustering Using a Kernel Function. ISMIS 2003: 417-421 - 2002
- [j16]Sadaaki Miyamoto, Arnold C. Alanzado:
Fuzzy c-Means and Mixture Distribution Models in the Presence of Noise Clusters. Int. J. Image Graph. 2(4): 573-586 (2002) - [j15]Vicenç Torra, Sadaaki Miyamoto:
Hierarchical Spherical Clustering. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 10(2): 157-172 (2002) - [c12]Sadaaki Miyamoto, Daisuke Suizu:
Fuzzy c-Means Clustering Using Transformations into High Dimensional Spaces. FSKD 2002: 656-660 - [c11]Sadaaki Miyamoto:
Generalized multisets and rough approximations. FUZZ-IEEE 2002: 751-756 - 2001
- [c10]Shigeyuki Takahara, Yoshiyuki Kusumoto, Sadaaki Miyamoto:
An Adaptive Meta-heuiristic Approach Using Partial Optimization to Non-convex Polygons Allocation Problem. FUZZ-IEEE 2001: 1191-1194 - [c9]Sadaaki Miyamoto:
Fuzzy Multisets and Fuzzy Clustering of Documents. FUZZ-IEEE 2001: 1539-1542 - [c8]Sadaaki Miyamoto:
Generalizations of Fuzzy Multisets for Including Infiniteness. JSAI Workshops 2001: 283-288 - [c7]Takatsugu Koga, Sadaaki Miyamoto, Osamu Takata:
Fuzzy c-Means and Mixture Distribution Model for Clustering Based on L1-Space. JSAI Workshops 2001: 289-294 - 2000
- [c6]Takahiro Kobayashi, Tetsuji Tani, Sadaaki Miyamoto:
Automation of reformer process in petroleum plant using fuzzy supervisory model predictive multivariable control system. FUZZ-IEEE 2000: 1021-1024 - [c5]Sadaaki Miyamoto:
Fuzzy Multisets and Their Generalizations. WMP 2000: 225-236
1990 – 1999
- 1999
- [j14]Takehisa Onisawa, Sadaaki Miyamoto:
Editorial: Applications of Soft Computing to Human-centered Information Systems. J. Adv. Comput. Intell. Intell. Informatics 3(1): 1-2 (1999) - [j13]Kazutaka Umayahara, Yoshiteru Nakamori, Sadaaki Miyamoto:
Fuzzy Clustering for Detecting Linear Structures with Different Dimensions. J. Adv. Comput. Intell. Intell. Informatics 3(1): 13-20 (1999) - [j12]Shigeyuki Takahara, Sadaaki Miyamoto:
An Adaptive Tabu Search (ATS) and Other Metaheuristics for a Class of Optimal Allocation Problems. J. Adv. Comput. Intell. Intell. Informatics 3(1): 21-27 (1999) - [j11]Tetsuji Tani, Takahiro Kobayashi, Sadaaki Miyamoto:
Hierarchical Control System with Fuzzy Supervisory System and PID Controller and Application to Large-Scale Hydrogen Gas Purity Control. J. Adv. Comput. Intell. Intell. Informatics 3(2): 126-130 (1999) - [c4]Sadaaki Miyamoto, Kazutaka Umayahara, Takeshi Nemoto:
Four c-Regression Methods and Classification Functions. RSFDGrC 1999: 203-211 - 1998
- [j10]Sadaaki Miyamoto:
Application of Rough Sets to Information Retrieval. J. Am. Soc. Inf. Sci. 49(3): 195-205 (1998) - [c3]Sadaaki Miyamoto:
An overview and new methods in fuzzy clustering. KES (1) 1998: 33-40 - [c2]Sadaaki Miyamoto, Masako Sato, Kazutaka Umayahara:
Generalization of discriminant analysis for possibility distributions. KES (3) 1998: 177-182 - 1996
- [j9]Sadaaki Miyamoto, Motohide Umano:
Editorial. Int. J. Intell. Syst. 11(9): 611-612 (1996) - 1990
- [j8]Sadaaki Miyamoto, Shinsuke Suga, Ko Oi:
Methods of digraph representation and cluster analysis for analyzing free association. IEEE Trans. Syst. Man Cybern. 20(3): 695-701 (1990)
1980 – 1989
- 1989
- [j7]Sadaaki Miyamoto:
Two approaches for information retrieval through fuzzy associations. IEEE Trans. Syst. Man Cybern. 19(1): 123-130 (1989) - 1986
- [j6]Sadaaki Miyamoto, Ko Oi, Osamu Abe, Atsuo Katsuya, Kazuhiko Nakayama:
Directed Graph Representations of Association Structures: A Systematic Approach. IEEE Trans. Syst. Man Cybern. 16(1): 53-61 (1986) - [j5]Sadaaki Miyamoto, Kazuhiko Nakayama:
Fuzzy Information Retrieval Based on a Fuzzy Pseudothesaurus. IEEE Trans. Syst. Man Cybern. 16(2): 278-282 (1986) - [j4]Sadaaki Miyamoto, Kazuhiko Nakayama:
Similarity Measures Based on a Fuzzy Set Model and Application to Hierarchical Clustering. IEEE Trans. Syst. Man Cybern. 16(3): 479-482 (1986) - [c1]Y. Asayama, Sadaaki Miyamoto, Ko Oi, Y. Ikebe:
Least square method for enhancement of laser radar images based on piecewise linear transformations of gray scales. ICASSP 1986: 1513-1516 - 1984
- [j3]Sadaaki Miyamoto, Kazuhiko Nakayama:
A directed graph representation based on a statistical hypothesis testing and application to citation and association structures. IEEE Trans. Syst. Man Cybern. 14(2): 203-212 (1984) - 1983
- [j2]Sadaaki Miyamoto, Teruhisa Miyake, Kazuhiko Nakayama:
Generation of a pseudothesaurus for information retrieval based on cooccurrences and fuzzy set operations. IEEE Trans. Syst. Man Cybern. 13(1): 62-70 (1983) - 1981
- [j1]Sadaaki Miyamoto, Kazuhiko Nakayama:
Determination of the conservation time of periodicals for optimal shelf maintenance of a library. J. Am. Soc. Inf. Sci. 32(4): 268-274 (1981)
Coauthor Index
[c131] [c128] [j70] [c127] [c126] [c125] [j68] [c124] [c123] [c121] [c120] [c114] [j60] [j59] [j56] [c98] [j55] [j53] [j51] [j50] [c95] [c94] [c93] [c92] [c87] [j47] [j46] [c85] [c84] [c83] [c81] [c78] [c76] [j44] [j43] [c73] [c72] [c70] [c69] [c68] [c66] [c65] [c60] [j42] [j36] [c57] [c56] [c55] [c53] [c52] [j35] [j33] [c50] [c49] [c44] [j29] [c39] [c37] [c33] [c21]
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