Using mega-fuzzification and data trend estimation in small data set learning for early FMS scheduling knowledge. - Der-Chiang Li; Chih-Sen Wu; Tung-I Tsai; Fengming M. Chang (Comput. Oper. Res., 2006)

Using mega-trend-diffusion and artificial samples in small data set learning for early flexible manufacturing system scheduling knowledge. - Der-Chiang Li; Chih-Sen Wu; Tung-I Tsai; Yao-San Lin (Comput. Oper. Res., 2007)

Acquiring knowledge with limited experience. - Der-Chiang Li; Chun-Wu Yeh; Tung-I Tsai; Yao-Hwei Fang; Susan C. Hu (Expert Syst. J. Knowl. Eng., 2007)

A new method to help diagnose cancers for small sample size. - Der-Chiang Li; Hung-Chang Hsu; Tung-I Tsai; Te-Jung Lu; Susan C. Hu (Expert Syst. Appl., 2007)

Approximate modeling for high order non-linear functions using small sample sets. - Tung-I Tsai; Der-Chiang Li (Expert Syst. Appl., 2008)

Utilize bootstrap in small data set learning for pilot run modeling of manufacturing systems. - Tung-I Tsai; Der-Chiang Li (Expert Syst. Appl., 2008)

A new approach to prediction of radiotherapy of bladder cancer cells in small dataset analysis. - Gy-Yi Chao; Tung-I Tsai; Te-Jung Lu; Hung-Chang Hsu; Bo-Ying Bao; Wan-Yu Wu; Miao-Ting Lin; Te-Ling Lu (Expert Syst. Appl., 2011)

A Learning Approach with Under-and Over-Sampling for Imbalanced Data Sets. - Chun-Wu Yeh; Der-Chiang Li; Liang-Sian Lin; Tung-I Tsai (IIAI-AAI, 2016)

Improving the Learning Accuracy of the Mega Trend Diffusion Technique for Small Data Sets. - Tung-I Tsai; Chun-Wu Yeh; Liang-Sian Lin; I-Hsiang Wen (IIAI-AAI, 2019)

Learning class-imbalanced data with region-impurity synthetic minority oversampling technique. - Der-Chiang Li; Ssu-Yang Wang; Kuan-Cheng Huang; Tung-I Tsai (Inf. Sci., 2022)