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Tae-Chon Ahn
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2020 – today
- 2020
- [j13]Seok-Beom Roh
, Yong-Soo Kim
Lazy Learning for Nonparametric Locally Weighted Regression. Int. J. Fuzzy Log. Intell. Syst. 20(2): 145-155 (2020)
2010 – 2019
- 2019
- [j12]Tae-Chon Ahn
Prototypes Reduction and Feature Selection based on Fuzzy Boundary Area for Nearest Neighbor Classifiers. Int. J. Fuzzy Syst. 21(2): 639-654 (2019) - 2014
- [j11]Seok-Beom Roh, Witold Pedrycz, Tae-Chon Ahn:
A design of granular fuzzy classifier. Expert Syst. Appl. 41(15): 6786-6795 (2014) - [p1]Tae-Chon Ahn, Seok-Beom Roh, Zi Long Yin
Design of Radial Basis Function Classifier Based on Polynomial Neural Networks. Soft Computing in Artificial Intelligence 2014: 107-115 - 2012
- [j10]Seok-Beom Roh, Tae-Chon Ahn, Witold Pedrycz:
Fuzzy linear regression based on Polynomial Neural Networks. Expert Syst. Appl. 39(10): 8909-8928 (2012) - 2011
- [j9]Seok-Beom Roh, Ji-Won Jeong, Tae-Chon Ahn:
Fuzzy Learning Vector Quantization based on Fuzzy k-Nearest Neighbor Prototypes. Int. J. Fuzzy Log. Intell. Syst. 11(2): 84-88 (2011) - 2010
- [j8]Seok-Beom Roh, Tae-Chon Ahn, Witold Pedrycz:
The design methodology of radial basis function neural networks based on fuzzy K-nearest neighbors approach. Fuzzy Sets Syst. 161(13): 1803-1822 (2010) - [j7]Seok-Beom Roh, Tae-Chon Ahn, Witold Pedrycz:
The Refinement of Models With the Aid of the Fuzzy k -Nearest Neighbors Approach. IEEE Trans. Instrum. Meas. 59(3): 604-615 (2010)
2000 – 2009
- 2007
- [j6]Sung-Kwun Oh, Seok-Beom Roh, Witold Pedrycz, Tae-Chon Ahn:
IG-based genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons. Neurocomputing 70(16-18): 2783-2798 (2007) - [c21]Zhong-Xian Wang, Tae-Chon Ahn:
Design of Adaptive Fuzzy-PI Control with the Aid of Rough Set Theory and Its Application to a HVDC System. ICIC (1) 2007: 433-444 - [c20]Seok-Beom Roh, Sung-Kwun Oh, Tae-Chon Ahn:
GA-Driven Fuzzy Set-Based Polynomial Neural Networks with Information Granules for Multi-variable Software Process. ISNN (2) 2007: 186-195 - [c19]Seok-Beom Roh, Tae-Chon Ahn:
Fuzzy Combined Polynomial Neural Networks. KES (3) 2007: 49-56 - 2006
- [j5]Jong-Seok Lee, Kyung-Won Jang, Tae-Chon Ahn:
Optimal Fuzzy Models with the Aid of SAHN-based Algorithm. Int. J. Fuzzy Log. Intell. Syst. 6(2): 138-143 (2006) - [j4]Tae-Chon Ahn, Kyung-Won Jang, Dong-Du Shin, Hak-Soo Kang, Yang-Woong Yoon:
Data Pattern Estimation with Movement of the Center of Gravity. Int. J. Fuzzy Log. Intell. Syst. 6(3): 210-216 (2006) - [j3]Tae-Chon Ahn, Kul Hur, Kyung-Won Jang:
Intuitionistic Fuzzy Subgroups and Level Subgroups. Int. J. Fuzzy Log. Intell. Syst. 6(3): 240-246 (2006) - [c18]Ho-Sung Park, Sung-Kwun Oh, Tae-Chon Ahn:
Improvement of HSOFPNN Using Evolutionary Algorithm. Australian Conference on Artificial Intelligence 2006: 818-825 - [c17]Ho-Sung Park, Tae-Chon Ahn:
The Analysis and Design of IG_gHSOFPNN by Evolutionary Optimization. FSKD 2006: 231-240 - [c16]Seok-Beom Roh, Hyung-Soo Hwang, Tae-Chon Ahn:
An Advanced Design Methodology of Fuzzy Set-Based Polynomial Neural Networks with the Aid of Symbolic Gene Type Genetic Algorithms and Information Granulation. ICONIP (3) 2006: 993-1001 - [c15]Ho-Sung Park, Kyung-Won Jang, Sung-Kwun Oh, Tae-Chon Ahn:
Design Methodology of Optimized IG_gHSOFPNN and Its Application to pH Neutralization Process. ICONIP (3) 2006: 1079-1086 - [c14]Tae-Chon Ahn, Ho-Sung Park:
Evolutionary Design of gdSOFPNN for Modeling and Prediction of NOx Emission Process. IDEAL 2006: 133-138 - [c13]Ho-Sung Park, Sung-Kwun Oh, Tae-Chon Ahn:
Optimization of Self-organizing Fuzzy Polynomial Neural Networks with the Aid of Granular Computing and Evolutionary Algorithm. IEA/AIE 2006: 472-477 - [c12]Seok-Beom Roh, Sung-Kwun Oh, Tae-Chon Ahn:
A New Design Methodology of Fuzzy Set-Based Polynomial Neural Networks with Symbolic Gene Type Genetic Algorithms. ISNN (1) 2006: 768-773 - [c11]Ho-Sung Park, Sung-Kwun Oh, Tae-Chon Ahn:
A Novel Self-Organizing Fuzzy Polynomial Neural Networks with Evolutionary FPNs: Design and Analysis. ISNN (1) 2006: 780-785 - [c10]Zhong-Xian Wang, Jueng-je Yang, Tae-Chon Ahn:
The Design of Self-tuning Strategy of Genetically Optimized Fuzzy-PI Controller for HVDC System. KES (1) 2006: 52-59 - [c9]Tae-Chon Ahn, Kyung-Won Jang, Seok-Beom Roh:
Genetically Optimized Fuzzy Set-Based Polynomial Neural Networks Based on Information Granules with Aids of Symbolic Genetic Algorithms. KES (3) 2006: 219-224 - 2005
- [c8]Sung-Kwun Oh, Keon-Jun Park, Witold Pedrycz, Tae-Chon Ahn:
Design of Information Granules-Based Fuzzy Systems Using Clustering Algorithm and Genetic Optimization. Australian Conference on Artificial Intelligence 2005: 1142-1145 - [c7]Sung-Kwun Oh, Byoung-Jun Park, Witold Pedrycz, Tae-Chon Ahn:
Genetically Optimized Hybrid Fuzzy Neural Networks Based on Simplified Fuzzy Inference Rules and Polynomial Neurons. International Conference on Computational Science (1) 2005: 798-803 - [c6]Sung-Kwun Oh, Seok-Beom Roh, Tae-Chon Ahn:
Parameter Estimation of Fuzzy Controller Using Genetic Optimization and Neurofuzzy Networks. ISNN (3) 2005: 107-112 - [c5]Sung-Kwun Oh, Keon-Jun Park, Yong-Soo Kim, Tae-Chon Ahn:
Identification of Fuzzy Systems with the Aid of Genetic Fuzzy Granulation. IWANN 2005: 391-398 - 2004
- [j2]Sung-Kwun Oh, Witold Pedrycz, Seok-Beom Roh, Tae-Chon Ahn:
Parameter estimation of fuzzy controller and its application to inverted pendulum. Eng. Appl. Artif. Intell. 17(1): 37-60 (2004) - [c4]Byoung-Jun Park, Sung-Kwun Oh, Witold Pedrycz, Tae-Chon Ahn:
Information Granulation-Based Multi-layer Hybrid Fuzzy Neural Networks: Analysis and Design. International Conference on Computational Science 2004: 188-195 - 2003
- [c3]Sung-Kwun Oh, James F. Peters, Witold Pedrycz, Tae-Chon Ahn:
Genetically Optimized Rule-Based Fuzzy Polynomial Neural Networks: Synthesis of Computational Intelligence Technologies. RSFDGrC 2003: 437-444 - 2002
- [j1]Sung-Kwun Oh, Witold Pedrycz, Tae-Chon Ahn:
Self-organizing neural networks with fuzzy polynomial neurons. Appl. Soft Comput. 2(1): 1-10 (2002) - [c2]Sheela Ramanna, James F. Peters, Tae-Chon Ahn:
Software Quality Knowledge Discovery: A Rough Set Approach. COMPSAC 2002: 1140-1145 - [c1]James F. Peters, Tae-Chon Ahn, Maciej Borkowski:
Obstacle Classification by a Line-Crawling Robot: A Rough Neurocomputing Approach. Rough Sets and Current Trends in Computing 2002: 594-601
Coauthor Index
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