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2020 – today
- 2024
[j10]Keiji Tatsumi
, Ryota Masui, Haruhisa Miyahara, Yeboon Yun:
Multiclass piecewise-linear SVMs with the restricted feasible region for the reinforcement degrees in constructing large-scale structures. Knowl. Based Syst. 300: 112197 (2024)- [c18]Keiji Tatsumi, Satoshi Maruyama, Yeboon Yun:
Multiclass piecewise-linear SVMs based on division of data space for determining the reinforcement degrees of large-scale structures. IJCNN 2024: 1-6 - 2022
- [j9]Keiji Tatsumi, Shunsuke Tsujioka, Ryota Masui, Yoshifumi Kusunoki, Yeboon Yun:
Determination of reinforcement degrees in constructing large-scale structures by using multiclass support vector machines. Knowl. Based Syst. 249: 108807 (2022) - 2021
- [c17]Chang Lu, Yeboon Yun, Min Yoon:
Application of Machine Learning to the Prediction of WBGT. SICE 2021: 3-8 - [c16]Keiji Tatsumi, Ryota Masui, Shunsuke Tsujioka, Yoshifumi Kusunoki, Yeboon Yun:
Multiclass Support Vector Machines for Determination of Reinforcement Degree in Constructing Large-scale Structures Based on Data Characteristics. SMC 2021: 1513-1518
2010 – 2019
- 2018
- [c15]Yeboon Yun, Hirotaka Nakayama, Min Yoon:
Multi-Objective Model Predictive Control. SCIS&ISIS 2018: 304-308 - 2016
- [j8]Yeboon Yun, Hirotaka Nakayama, Min Yoon:
Generation of Pareto optimal solutions using generalized DEA and PSO. J. Glob. Optim. 64(1): 49-61 (2016) - 2013
- [j7]Yeboon Yun, Hirotaka Nakayama:
Utilizing expected improvement and generalized data envelopment analysis in multi-objective genetic algorithms. J. Glob. Optim. 57(2): 367-384 (2013) - 2012
- [c14]Yeboon Yun, Kohei Furukawa, Takeshi Iida, Hirotaka Nakayama:
Evaluation of sewerage systems using data envelopment analysis. SCIS&ISIS 2012: 733-737 - [c13]Hirotaka Nakayama, Yeboon Yun, Yuki Uno:
Parameter tuning of large scale support vector machines using ensemble learning with applications to imbalanced data sets. SMC 2012: 2815-2820 - 2011
- [c12]Yeboon Yun, Hirotaka Nakayama, Min Yoon:
Evolutionary multi-objective optimization using expected improvement and generalized DEA. SMC 2011: 663-668 - 2010
- [c11]Junya Nishiguchi, Chosei Kaseda, Hirotaka Nakayama, Masao Arakawa, Yeboon Yun:
Modified Support Vector Regression in outlier detection. IJCNN 2010: 1-5
2000 – 2009
- 2009
- [b1]Min Yoon, Yeboon Yun, Hirotaka Nakayama:
Sequential Approximate Multiobjective Optimization Using Computational Intelligence. Vector Optimization, Springer 2009, ISBN 978-3-540-88909-0, pp. 1-183 - 2008
- [c10]Junya Nishiguchi, Chosei Kaseda, Hirotaka Nakayama, Masao Arakawa, Yeboon Yun:
Practical Approach to Outlier Detection Using Support Vector Regression. ICONIP (1) 2008: 995-1001 - [c9]Hirotaka Nakayama, Yeboon Yun:
Multi-objective Model Predictive Optimization using Computational Intelligence. IFIP AI 2008: 319-328 - [c8]Hirotaka Nakayama, Yeboon Yun, Masakazu Shirakawa:
Multi-objective Model Predictive Control. MCDM 2008: 277-287 - 2007
- [c7]Hirotaka Nakayama, Yeboon Yun:
Combining Aspiration Level Methods in Multi-objective Programming and Sequential Approximate Optimization using Computational Intelligence. MCDM 2007: 319-324 - [c6]Yeboon Yun, Hirotaka Nakayama, Min Yoon:
Sequential Approximation Method in Multi-objective Optimization Using Aspiration Level Approach. EMO 2007: 317-329 - 2006
- [c5]Hirotaka Nakayama, Yeboon Yun:
Support Vector Regression Based on Goal Programming and Multi-objective Programming. IJCNN 2006: 1156-1161 - [p1]Hirotaka Nakayama, Yeboon Yun:
Generating Support Vector Machines Using Multi-Objective Optimization and Goal Programming. Multi-Objective Machine Learning 2006: 173-198 - 2005
- [j6]Hirotaka Nakayama, Yeboon Yun, Takeshi Asada, Min Yoon:
MOP/GP models for machine learning. Eur. J. Oper. Res. 166(3): 756-768 (2005) - [c4]Yeboon Yun, Min Yoon, Hirotaka Nakayama:
Genetic Algorithm for Multi-objective Optimization Using GDEA. ICNC (3) 2005: 409-416 - 2004
- [j5]Takeshi Asada, Yeboon Yun, Hirotaka Nakayama, Tetsuzo Tanino:
Pattern classification by goal programming and support vector machines. Comput. Manag. Sci. 1(3-4): 211-230 (2004) - [j4]Yeboon Yun, Hirotaka Nakayama, Tetsuzo Tanino:
A generalized model for data envelopment analysis. Eur. J. Oper. Res. 157(1): 87-105 (2004) - [j3]Yeboon Yun, Hirotaka Nakayama, Masao Arakawa:
Multiple criteria decision making with generalized DEA and an aspiration level method. Eur. J. Oper. Res. 158(3): 697-706 (2004) - [j2]Min Yoon, Yeboon Yun, Hirotaka Nakayama:
Total Margin Algorithms in Support Vector Machines. IEICE Trans. Inf. Syst. 87-D(5): 1223-1230 (2004) - [c3]Yeboon Yun, Masao Arakawa, Hirotaka Nakayama:
Fitness evaluation using generalized data envelopment analysis in MOGA. IEEE Congress on Evolutionary Computation 2004: 464-471 - [c2]Yeboon Yun, Min Yoon, Hirotaka Nakayama, Wataru Shiraki:
Prediction of Business Failure by Total Margin Support Vector Machines. KES 2004: 441-448 - 2003
- [c1]Hirotaka Nakayama, Yeboon Yun, Takeshi Asada, Min Yoon:
Goal Programming Approaches to Support Vector Machines. KES 2003: 356-363 - 2001
- [j1]Yeboon Yun, Hirotaka Nakayama, Tetsuzo Tanino, Masao Arakawa:
Generation of efficient frontiers in multi-objective optimization problems by generalized data envelopment analysis. Eur. J. Oper. Res. 129(3): 586-595 (2001)
Coauthor Index
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