Using virtual sample generation to build up management knowledge in the early manufacturing stages. - Der-Chang Li; Yao-San Lin (Eur. J. 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)

Learning management knowledge for manufacturing systems in the early stages using time series data. - Der-Chiang Li; Yao-San Lin (Eur. J. Oper. Res., 2008)

Constructing marketing decision support systems using data diffusion technology: A case study of gas station diversification. - Der-Chiang Li; Yao-San Lin; Yu-Cheng Huang (Expert Syst. Appl., 2009)

The Generalized-Trend-Diffusion modeling algorithm for small data sets in the early stages of manufacturing systems. - Yao-San Lin; Der-Chiang Li (Eur. J. Oper. Res., 2010)

A non-linear quality improvement model using SVR for manufacturing TFT-LCDs. - Der-Chiang Li; Wen-Chih Chen; Chiao-Wen Liu; Yao-San Lin (J. Intell. Manuf., 2012)

Non-parametric Statistical Assistance in Virtual Sample Selection for Small Data Set Prediction. - Yao-San Lin; Liang-Sian Lin; Der-Chiang Li; Wei-Lin Liao (ACIT-CSI, 2015)

Modeling with Insufficient Data to Increase Prediction Stability. - Yao-San Lin (IIAI-AAI, 2016)

Generating Synthetic Samples to Improve Small Sample Learning with Mixed Numerical and Categorical Attributes. - Yao-San Lin; Wan-Ni Cheng; Chien-Chih Chen; Der-Chiang Li; Hung-Yu Chen (IIAI-AAI, 2019)

A Boundary-Information-Based Oversampling Approach to Improve Learning Performance for Imbalanced Datasets. - Der-Chiang Li; Qi-Shi Shi; Yao-San Lin; Liang-Sian Lin (Entropy, 2022)

A Novel Classification Method Based on a Two-Phase Technique for Learning Imbalanced Text Data. - Der-Chiang Li; Szu-Chou Chen; Yao-San Lin; Wen-Yen Hsu (Symmetry, 2022)

An Integrated Framework Based on GAN and RBI for Learning with Insufficient Datasets. - Yao-San Lin; Liang-Sian Lin; Chih-Ching Chen (Symmetry, 2022)

Generating virtual samples to improve learning performance in small datasets with non-linear and asymmetric distributions. - Liang-Sian Lin; Yao-San Lin; Der-Chiang Li (Neurocomputing, 2023)

Mega trend diffusion-siamese network oversampling for imbalanced datasets' SVM classification. - Liang-Sian Lin; Yao-San Lin; Der-Chiang Li; Yi-Ting Chen (Appl. Soft Comput., 2023)

Improved learning performance for small datasets in high dimensions by new dual-net model for non-linear interpolation virtual sample generation. - Liang-Sian Lin; Yao-San Lin; Der-Chiang Li; Yun-Hsuan Liu (Decis. Support Syst., 2023)

Enhancing prediction accuracy for high-dimensional small-sample-size microarray data cancer by combining chebyshev interpolation with new dual-net GAN. - Liang-Sian Lin; Yao-San Lin; Der-Chiang Li; Susan C. Hu; Chih-I Huang (Appl. Soft Comput., 2025)