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2020 – today
- 2024
[c86]Yasunori Endo
, Kazuki Mori:
On Objective-Based Clustering from the Perspective of Transportation Problem. MDAI 2024: 90-100- 2023
- [j45]Yasunori Endo, Kanata Hoshino, Yukihiro Hamasuna:
On hard c-means with cluster radius that makes the cluster partition homotopy equivalent to weighted $$\alpha$$-complex. J. Ambient Intell. Humaniz. Comput. 14(11): 14995-15002 (2023) - 2021
- [c85]Yukihiro Hamasuna, Shusuke Nakano, Yasunori Endo:
Network Clustering with Controlled Node Size. MDAI 2021: 243-256 - 2020
- [c84]Jie Li, Yasunori Endo:
Fuzzy c-Means with Improved Particle Swarm Optimization. FUZZ-IEEE 2020: 1-8
2010 – 2019
- 2019
- [j44]Yusuke Oi, Yasunori Endo:
Kernel Fuzzy c-Regression Based on Least Absolute Deviation with Modified Huber Function. J. Adv. Comput. Intell. Intell. Informatics 23(3): 571-576 (2019) - [j43]Yukihiro Hamasuna, Shusuke Nakano, Ryo Ozaki, Yasunori Endo:
Cluster Validity Measures Based Agglomerative Hierarchical Clustering for Network Data. J. Adv. Comput. Intell. Intell. Informatics 23(3): 577-583 (2019) - 2018
- [j42]Yukihiro Hamasuna, Ryo Ozaki, Yasunori Endo:
Two-Stage Clustering Based on Cluster Validity Measures. J. Adv. Comput. Intell. Intell. Informatics 22(1): 54-61 (2018) - [j41]Yasunori Endo, Yukihiro Hamasuna, Tsubasa Hirano, Naohiko Kinoshita:
Even-Sized Clustering Based on Optimization and its Variants. J. Adv. Comput. Intell. Intell. Informatics 22(1): 62-69 (2018) - [j40]Kei Kitajima, Yasunori Endo, Yukihiro Hamasuna:
Fuzzified Even-Sized Clustering Based on Optimization. J. Adv. Comput. Intell. Intell. Informatics 22(4): 537-543 (2018) - [j39]Yukihiro Hamasuna, Daiki Kobayashi, Ryo Ozaki, Yasunori Endo:
Cluster Validity Measures for Network Data. J. Adv. Comput. Intell. Intell. Informatics 22(4): 544-550 (2018) - [c83]Sadaaki Miyamoto, Jong Moon Choi, Yasunori Endo, Van-Nam Huynh:
Optimal Clustering with Twofold Memberships. MDAI 2018: 221-231 - [c82]Yuya Kanazawa, Yasunori Endo, Shin-ichi Nakazawa, Daisuke Hijikata:
A Note on Brake System of Train Set with Wheel Slide Protection System. SCIS&ISIS 2018: 597-602 - [c81]Shusuke Nakano, Yukihiro Hamasuna, Yasunori Endo:
A Study on Controlled Node Sized Network Clustering for Unweighted Network Data. SCIS&ISIS 2018: 826-831 - [c80]Naoya Kimoto, Yasunori Endo:
On Linear Clustering with Constraints on Cluster Size. SCIS&ISIS 2018: 832-836 - [c79]Kei Kitajima, Yasunori Endo:
Even-Sized Clustering with Noise Clustering Method. SCIS&ISIS 2018: 837-842 - 2017
- [c78]Yasunori Endo, Naohiko Kinoshita:
Various Types of Objective-Based Rough Clustering. Fuzzy Sets, Rough Sets, Multisets and Clustering 2017: 63-85 - [c77]Yukihiro Hamasuna, Yasunori Endo:
On Some Clustering Algorithms Based on Tolerance. Fuzzy Sets, Rough Sets, Multisets and Clustering 2017: 87-99 - [c76]Yasunori Endo, Sachiko Ishida, Naohiko Kinoshita, Yukihiro Hamasuna:
On various types of controlled-sized clustering based on optimization. FUZZ-IEEE 2017: 1-6 - [c75]Ryosuke Abe, Sadaaki Miyamoto, Yasunori Endo, Yukihiro Hamasuna:
Hierarchical clustering algorithms with automatic estimation of the number of clusters. IFSA-SCIS 2017: 1-5 - [c74]Yasunori Endo, Sachiko Ishida, Naohiko Kinoshita:
Controlled-sized clustering based on optimization. IFSA-SCIS 2017: 1-6 - [c73]Yukihiro Hamasuna, Ryo Ozaki, Yasunori Endo:
A study on cluster validity measures for clustering network data. IFSA-SCIS 2017: 1-6 - [c72]Yoshitaka Maeda, Yasunori Endo, Sho Sanami:
On Cell Detection System with User Interaction. MDAI 2017: 195-206 - [c71]Ryo Ozaki, Yukihiro Hamasuna, Yasunori Endo:
Agglomerative hierarchical clustering based on local optimization for cluster validity measures. SMC 2017: 1822-1827 - 2016
- [j38]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) - [j37]Yasunori Endo, Tomoyuki Suzuki, Naohiko Kinoshita, Yukihiro Hamasuna:
On Fuzzy Non-Metric Model for Data with Tolerance and its Application to Incomplete Data Clustering. J. Adv. Comput. Intell. Intell. Informatics 20(4): 571-579 (2016) - [j36]Yukihiro Hamasuna, Naohiko Kinoshita, Yasunori Endo:
Comparison of Cluster Validity Measures Based x-Means. J. Adv. Comput. Intell. Intell. Informatics 20(5): 845-853 (2016) - [c70]Sadaaki Miyamoto, Yoshiyuki Komazaki, Yasunori Endo:
Generalizations of Fuzzy c-Means and Fuzzy Classifiers. IUKM 2016: 151-162 - [c69]Yasunori Endo, Tsubasa Hirano, Naohiko Kinoshita, Yukihiro Hamasuna:
On Various Types of Even-Sized Clustering Based on Optimization. MDAI 2016: 165-177 - [c68]Sadaaki Miyamoto, Yousuke Kaizu, Yasunori Endo:
Hierarchical and Non-Hierarchical Medoid Clustering Using Asymmetric Similarity Measures. SCIS&ISIS 2016: 400-403 - [c67]Tsubasa Hirano, Yasunori Endo, Naohiko Kinoshita, Sadaaki Miyamoto:
A Note on Even-Sized Clustering Based on Optimization. SCIS&ISIS 2016: 404-409 - [c66]Ryo Ozaki, Yukihiro Hamasuna, Yasunori Endo:
A Method of Two-Stage Clustering Based on Cluster Validity Measures. SCIS&ISIS 2016: 410-415 - [c65]Yukihiro Hamasuna, Yasunori Endo:
On Kernelized Sequential Hard Clustering. SCIS&ISIS 2016: 416-419 - 2015
- [j35]Yukihiro Hamasuna, Yasunori Endo:
On Cluster Extraction from Relational Data Using L1-Regularized Possibilistic Assignment Prototype Algorithm. J. Adv. Comput. Intell. Intell. Informatics 19(1): 23-28 (2015) - [j34]Naohiko Kinoshita, Yasunori Endo:
On Objective-Based Rough Hard and Fuzzy c-Means Clustering. J. Adv. Comput. Intell. Intell. Informatics 19(1): 29-35 (2015) - [j33]Akira Sugawara, Yasunori Endo, Naohiko Kinoshita:
On Objective-Based Rough c-Regression. J. Adv. Comput. Intell. Intell. Informatics 19(1): 36-42 (2015) - [j32]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) - [j31]Naohiko Kinoshita, Yasunori Endo, Yukihiro Hamasuna:
Fuzzy c-Means with Quadratic Penalty-Vector Regularization Using Kullback-Leibler Information for Uncertain Data. J. Adv. Comput. Intell. Intell. Informatics 19(5): 624-631 (2015) - [j30]Naohiko Kinoshita, Yasunori Endo, Ken Onishi:
On Objective-Based Rough Clustering with Fuzzy-Set Representation. J. Adv. Comput. Intell. Intell. Informatics 19(5): 632-638 (2015) - [j29]Toru Sano, Yasunori Endo, Shin-ichi Nakazawa, Daisuke Hijikata:
On Estimation of Tangential Force in Railways Brake Systems by Fuzzy Inference. J. Adv. Comput. Intell. Intell. Informatics 19(5): 639-644 (2015) - [j28]Yukihiro Hamasuna, Yasunori Endo:
On Sequential Cluster Extraction Based on L1-Regularized Possibilistic c-Means. J. Adv. Comput. Intell. Intell. Informatics 19(5): 655-661 (2015) - [j27]Yukihiro Hamasuna, Yasunori Endo:
On a Family of New Sequential Hard Clustering. J. Adv. Comput. Intell. Intell. Informatics 19(6): 759-765 (2015) - [j26]Naohiko Kinoshita, Yasunori Endo, Akira Sugawara:
On Hierarchical Linguistic-Based Clustering. J. Adv. Comput. Intell. Intell. Informatics 19(6): 900-906 (2015) - [c64]Yousuke Kaizu, Sadaaki Miyamoto, Yasunori Endo:
Hard and Fuzzy c-Medoids for Asymmetric Networks. IFSA-EUSFLAT 2015 - [c63]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 - [c62]Yasunori Endo, Sadaaki Miyamoto:
Spherical k-Means++ Clustering. MDAI 2015: 103-114 - [c61]Sadaaki Miyamoto, Ryosuke Abe, Yasunori Endo, Jun-ichi Takeshita:
Ward method of hierarchical clustering for non-Euclidean similarity measures. SoCPaR 2015: 60-63 - 2014
- [c60]Yukihiro Hamasuna, Yasunori Endo:
On new sequential hard c-means and its kernelization. GrC 2014: 82-87 - [c59]Akira Sugawara, Naohiko Kinoshita, Yasunori Endo:
On linguistic-based clustering. GrC 2014: 265-270 - [c58]Ken Onishi, Naohiko Kinoshita, Yasunori Endo:
A Note on Objective-Based Rough Clustering with Fuzzy-Set Representation. MDAI 2014: 122-134 - [c57]Yukihiro Hamasuna, Yasunori Endo:
Semi-Supervised Hard and Fuzzy c-Means with Assignment Prototype Term. MDAI 2014: 135-144 - [c56]Yasunori Endo, Naohiko Kinoshita, Kuniaki Iwakura, Yukihiro Hamasuna:
Hard and Fuzzy c-means Algorithms with Pairwise Constraints by Non-metric Terms. MDAI 2014: 145-157 - [c55]Yukihiro Hamasuna, Yasunori Endo:
On new sequential hard c-medoids. SCIS&ISIS 2014: 489-494 - [c54]Tsubasa Hirano, Yasunori Endo, Naohiko Kinoshita, Yukihiro Hamasuna:
On even-sized clustering algorithm based on optimization. SCIS&ISIS 2014: 495-500 - [c53]Naohiko Kinoshita, Yasunori Endo, Sadaaki Miyamoto:
On Some Models of Objective-Based Rough Clustering. WI-IAT (1) 2014: 392-399 - [e1]Vicenç Torra, Yasuo Narukawa, Yasunori Endo:
Modeling Decisions for Artificial Intelligence - 11th International Conference, MDAI 2014, Tokyo, Japan, October 29-31, 2014. Proceedings. Lecture Notes in Computer Science 8825, Springer 2014, ISBN 978-3-319-12053-9 [contents] - 2013
- [j25]Yasunori Endo, Naohiko Kinoshita:
Objective-Based Rough c-Means Clustering. Int. J. Intell. Syst. 28(9): 907-925 (2013) - [j24]Yasunori Endo, Ayako Heki, Yukihiro Hamasuna:
Non Metric Model Based on Rough Set Representation. J. Adv. Comput. Intell. Intell. Informatics 17(4): 540-551 (2013) - [j23]Yukihiro Hamasuna, Yasunori Endo:
On semi-supervised fuzzy c-means clustering for data with clusterwise tolerance by opposite criteria. Soft Comput. 17(1): 71-81 (2013) - [c52]Yukihiro Hamasuna, Yasunori Endo:
On Cluster Extraction from Relational Data Using Entropy Based Relational Crisp Possibilistic Clustering. KSE (2) 2013: 57-67 - [c51]Naohiko Kinoshita, Yasunori Endo:
EM-Based Clustering Algorithm for Uncertain Data. KSE (2) 2013: 69-81 - [c50]Yukihiro Hamasuna, Yasunori Endo:
On Sequential Cluster Extraction Based on L 1-Regularized Possibilistic Non-metric Model. MDAI 2013: 204-213 - [c49]Yasunori Endo, Akira Sugawara, Naohiko Kinoshita:
Rough c-Regression Based on Optimization of Objective Function. MDAI 2013: 272-283 - [c48]Yukihiro Hamasuna, Yasunori Endo:
Sequential Extraction by Using Two Types of Crisp Possibilistic Clustering. SMC 2013: 3505-3510 - 2012
- [j22]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) - [j21]Yasunori Endo:
On Entropy Based Fuzzy Non Metric Model ? Proposal, Kernelization and Pairwise Constraints ?. J. Adv. Comput. Intell. Intell. Informatics 16(1): 169-173 (2012) - [j20]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) - [j19]Yukihiro Hamasuna, Yasunori Endo:
Comparison of Semi-Supervised Hierarchical Clustering Using Clusterwise Tolerance. J. Adv. Comput. Intell. Intell. Informatics 16(7): 819-824 (2012) - [j18]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) - [j17]Yasunori Endo, Arisa Taniguchi, Yukihiro Hamasuna:
Hard c-Means Using Quadratic Penalty-Vector Regularization for Uncertain Data. J. Adv. Comput. Intell. Intell. Informatics 16(7): 831-840 (2012) - [c47]Yuchi Kanzawa, Yasunori Endo:
On FNM-based and RFCM-based fuzzy co-clustering algorithms. FUZZ-IEEE 2012: 1-8 - [c46]Yasunori Endo, Naohiko Kinoshita:
On objective-based rough c-means clustering. GrC 2012: 1-6 - [c45]Yasunori Endo, Ayako Heki, Yukihiro Hamasuna:
On Rough Set Based Non Metric Model. MDAI 2012: 394-407 - [c44]Ayako Heki, Yasunori Endo, Sadaaki Miyamoto:
Rough set based non metric model. SCIS&ISIS 2012: 1778-1783 - [c43]Yukihiro Hamasuna, Yasunori Endo:
On sparse possibilistic clustering with crispness - Classification function and sequential extraction. SCIS&ISIS 2012: 1801-1806 - 2011
- [j16]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) - [j15]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) - [j14]Yasunori Endo, Yasushi Hasegawa, Yukihiro Hamasuna, Yuchi Kanzawa:
Fuzzy c-Means Clustering for Uncertain Data Using Quadratic Penalty-Vector Regularization. J. Adv. Comput. Intell. Intell. Informatics 15(1): 76-82 (2011) - [j13]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) - [j12]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) - [c42]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 - [c41]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 - [c40]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
On hard and fuzzy c-means clustering with conditionally positive definite kernel. FUZZ-IEEE 2011: 816-820 - [c39]Yasunori Endo, Tatsuyoshi Tsuji, Yukihiro Hamasuna, Kouta Kurihara:
On principal component analysis for data with tolerance. GrC 2011: 177-182 - [c38]Yukihiro Hamasuna, Yasunori Endo:
On semi-supervised fuzzy c-means clustering with clusterwise tolerance by opposite criteria. GrC 2011: 225-230 - [c37]Aoi Takahashi, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy c-means clustering for data with tolerance using cosine correlation. GrC 2011: 619-624 - [c36]Yasunori Endo, Yukihiro Hamasuna:
Hard and fuzzy c-means clustering with mutual relation constraints. ISDA 2011: 557-562 - [c35]Yasunori Endo, Yukihiro Hamasuna:
Fuzzy c-Means Clustering with Mutual Relation Constraints - Construction of Two Types of Algorithms. KES (1) 2011: 131-140 - [c34]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Semi-supervised Agglomerative Hierarchical Clustering with Ward Method Using Clusterwise Tolerance. MDAI 2011: 103-113 - [c33]Yasunori Endo, Arisa Taniguchi, Aoi Takahashi, Yukihiro Hamasuna:
On Hard c-Means Using Quadratic Penalty-Vector Regularization for Uncertain Data. MDAI 2011: 126-138 - 2010
- [j11]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
On tolerant fuzzy c-means clustering and tolerant possibilistic clustering. Soft Comput. 14(5): 487-494 (2010) - [j10]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) - [c32]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 - [c31]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Cluster validity measures for data with tolerance. FUZZ-IEEE 2010: 1-6 - [c30]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 - [c29]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Semi-supervised Fuzzy c-Means Clustering Using Clusterwise Tolerance Based Pairwise Constraints. GrC 2010: 188-193 - [c28]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Indefinite Kernel Fuzzy c-Means Clustering Algorithms. MDAI 2010: 116-128 - [c27]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Semi-supervised Agglomerative Hierarchical Clustering Using Clusterwise Tolerance Based Pairwise Constraints. MDAI 2010: 152-162
2000 – 2009
- 2009
- [j9]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
On Tolerant Fuzzy c -Means Clustering. J. Adv. Comput. Intell. Intell. Informatics 13(4): 421-428 (2009) - [j8]Makito Yamashiro, Yasunori Endo, Yukihiro Hamasuna:
Clustering Algorithm Based on Probabilistic Dissimilarity. J. Adv. Comput. Intell. Intell. Informatics 13(4): 429-433 (2009) - [j7]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) - [c26]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy c-Lines for Data with Tolerance. IFSA/EUSFLAT Conf. 2009: 861-866 - [c25]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
On Tolerant Fuzzy c-Means Clustering with L1-Regularization. IFSA/EUSFLAT Conf. 2009: 1152-1157 - [c24]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Entropy regularized fuzzy C-lines for data with tolerance. FUZZ-IEEE 2009: 1113-1118 - [c23]Yasunori Endo, Yukihiro Hamasuna, Makito Yamashiro, Sadaaki Miyamoto:
On semi-supervised fuzzy c-means clustering. FUZZ-IEEE 2009: 1119-1124 - [c22]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
On L1-Norm based tolerant fuzzy c-Means clustering. FUZZ-IEEE 2009: 1125-1130 - [c21]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 - [c20]Yukihiro Hamasuna, Yasunori Endo, Sadaaki Miyamoto:
Comparison of tolerant fuzzy c-means clustering with L2- and L1-regularization. GrC 2009: 197-202 - [c19]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Some Pairwise Constrained Semi-Supervised Fuzzy c-Means Clustering Algorithms. MDAI 2009: 268-281 - 2008
- [j6]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) - [j5]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) - [c18]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 - [c17]Vicenç Torra, Sadaaki Miyamoto, Yasunori Endo, Josep Domingo-Ferrer:
On intuitionistic fuzzy clustering for its application to privacy. FUZZ-IEEE 2008: 1042-1048 - [c16]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy classification function of fuzzy c-means algorithms for data with tolerance. FUZZ-IEEE 2008: 1081-1088 - [c15]Yukihiro Hamasuna, Yasunori Endo, Makito Yamashiro:
On Tolerant Entropy Regularized Fuzzy C-means. GrC 2008: 244-247 - [c14]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 - [c13]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 - 2007
- [j4]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) - [j3]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) - [c12]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 - [c11]Yasunori Endo, Yukihiro Hamasuna, Sadaaki Miyamoto:
Agglomerative Hierarchical Clustering for Data with Tolerance. GrC 2007: 404-409 - [c10]Yasushi Hasegawa, Yasunori Endo, Yukihiro Hamasuna, Sadaaki Miyamoto:
Fuzzy c -Means for Data with Tolerance Defined as Hyper-Rectangle. MDAI 2007: 237-248 - 2006
- [j2]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) - [c9]Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto:
Fuzzy c-Means Clustering for Data with Tolerance Using Kernel Functions. FUZZ-IEEE 2006: 744-750 - [c8]Koji Toduka, Yasunori Endo:
Fuzzy K-nearest Neighbor and its Application to Recognize of the Driving Environment. FUZZ-IEEE 2006: 751-756 - [c7]Yasunori Endo, Ryuichi Murata, Hiromi Toyoda, Sadaaki Miyamoto:
L1-Norm based Fuzzy Clustering for Data with Tolerance. FUZZ-IEEE 2006: 770-777 - [c6]Ryuichi Murata, Yasunori Endo, Hideyuki Haruyama, Sadaaki Miyamoto:
On Fuzzy c-Means for Data with Tolerance. MDAI 2006: 351-361 - 2005
- [c5]Yasunori Endo, Hayato Iwata:
On Dynamic Clustering and Two Options. FUZZ-IEEE 2005: 996-1001 - [c4]Tetsuya Asanome, Toshiaki Nonaka, Yasunori Endo, Shin-ichi Nakazawa, Hiroshi Yoshikawa:
Evaluation of Control Performance of Multi-stage Fuzzy Reasoning in Anti-lock Braking System for Railways Using Fuzzy Reasoning. MDAI 2005: 110-121 - [c3]Yasunori Endo, Hayato Iwata:
Dynamic Clustering Based on Universal Gravitation Model. MDAI 2005: 183-193 - [c2]Sadaaki Miyamoto, Yasunori Endo, Satoshi Hayakawa, Erina Kataoka:
Classification and clustering of information objects based on fuzzy neighborhood system. SMC 2005: 3210-3215 - 2004
- [j1]Yasunori Endo, Kazuo Horiuchi:
Risk analysis of fuzzy control systems with (n+1)-inputs and 1-output FLC. Fuzzy Sets Syst. 147(3): 341-361 (2004) - [c1]Yasunori Endo, Hideyuki Haruyama, Takayoshi Okubo:
On some hierarchical clustering algorithms using kernel functions. FUZZ-IEEE 2004: 1513-1518
Coauthor Index
[j45] [c85] [j43] [j42] [j41] [j40] [j39] [c81] [c77] [c76] [c75] [c73] [c71] [j37] [j36] [c69] [c66] [c65] [j35] [j31] [j28] [j27] [c63] [c60] [c57] [c56] [c55] [c54] [j24] [j23] [c52] [c50] [c48] [j20] [j19] [j17] [c45] [c43] [j15] [j14] [c42] [c41] [c39] [c38] [c36] [c35] [c34] [c33] [j11] [c32] [c31] [c29] [c27] [j9] [j8] [c25] [c23] [c22] [c21] [c20] [j5] [c18] [c15] [j3] [c12] [c11] [c10]
[c83] [c75] [j38] [c70] [c68] [c67] [j32] [c64] [c63] [c62] [c61] [c53] [j22] [j20] [j18] [c44] [j16] [j15] [j13] [j12] [c42] [c41] [c40] [c37] [c34] [j11] [j10] [c32] [c31] [c30] [c29] [c28] [c27] [j9] [j7] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [j6] [j5] [c18] [c17] [c16] [c14] [c13] [j4] [j3] [c12] [c11] [c10] [j2] [c9] [c7] [c6] [c2]
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last updated on 2025-01-21 00:14 CET by the dblp team
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