國立暨南國際大學資訊管理學系 > 系所介紹-師資介紹 > 系所介紹-師資介紹-白炳豐

系所介紹

本系特色

師資介紹

空間設備

地理位置

特聘教授

白炳豐

學歷

美國堪薩斯州立大學 工業與製造系統工程博士

研究領域

機器(深度)學習, 類神經網路,模型參數最佳化,大數據分析

實驗室

智慧型資訊系統與管理實驗室

期刊論文

  1. Wun-Tsong Chaou, Yu-Hui Liu, Ying-Lei Lin, Chao-Chien Huang, Ping-Feng Pai* (2026, Mar). Machine Learning-Based Models for Identifying Learning Disabilities. Electronics , 15(6), 1278, 1-21. (SCIE).
  2. You-Jeng Chang, Ying-Lei Lin, Ping-Feng Pai* (2025, May). Support Vector Machines with Hyperparameter Optimization Frameworks for Classifying Mobile Phone Prices in Multi-Class. Electronics, 14(11), 2173,1-21. (SCIE). 
  3. Jung-Pin Lai, Shane Lin, Vito Lin, Andrew Kang,Yu-Po Wang, Ping-Feng Pai* (2025, Mar). Predicting Thermal Resistance of Packaging Design by Machine Learning Models. Micromachines, 16(3), 350,1-15. (SCIE).
  4. Wan-Lu Hsu, Ying-Lei Lin, Jung-Pin Lai, Yu-Hui Liu, Ping-Feng Pai* (2025, Jan). Forecasting Corporate Financial Performance Using Deep Learning with Environmental, Social, and Governance Data. Electronics, 14(3), 417, 1-23. (SCIE).
  5. Li-Hsing Lai, Ying-Lei Lin , Yu-Hui Liu, Jung-Pin Lai , Wen-Chieh Yang, Hung-Pin Hou, Ping-Feng Pai* (2024, Dec). The Use of Machine Learning Models with Optuna in Disease Prediction. Electronics, 13(23), 4775. (SCIE).
  6. Ming-Jr Tsai, Chung-Hui Lin, Jung-Pin Lai, Ping-Feng Pai* (2024, Nov). Using Deep Learning, Optuna, and Digital Images to Identify Necrotizing Fasciitis. Electronics, 13(22), 4421. (SCIE).
  7. Chieh-Huang Chen, Ying-Lei Lin, Ping-Feng Pai* (2024, Sep). Forecasting Flower Prices by Long Short-Term Memory Model with Optuna. Electronics, 13(18), 3646. (SCIE).
  8. Wen-Chieh Yang, Jung-Pin Lai, Yu-Hui Liu, Ying-Lei Lin, Hung-Pin Hou, Ping-Feng
    Pai* (2023, Dec.). Using Medical Data and Clustering Techniques for a Smart
    Healthcare System. Electronics, 13(1), 140, 1-20, (SCIE)
  9. Chieh-Huang Chen , Jung-Pin Lai, Yu-Ming Chang, Chi-Ju Lai, Ping-Feng Pai*
    (2023, Jul). A Study of Optimization in Deep Neural Networks for Regression.
    Electronics, 12(14), 3071, 1-17. (SCIE)
  10. Yu-Shan Li, Ping-Feng Pai*, Ying-Lei Lin (2023, Mar). Forecasting inflations by
    extreme gradient boosting with the genetic algorithm. Journal of Ambient Intelligence
    and Humanized Computing, 14(3),2211-2220. (EI)
  11. Jung-Pin Lai, Ping-Feng Pai* (2023, Feb). A Dual Long Short-Term Memory Model
    in Forecasting the Number of COVID-19 Infections. Electronics, 12(3),759,1-13.
    (SCIE)
  12. Jung-Pin Lai, Ying-Lei Lin, Ho-Chuan Lin, Chih-Yuan Shih, Yu-Po Wang, Ping- Feng
    Pai* (2023, Feb). Tree-Based Machine Learning Models with Optuna in Predicting
    Impedance Values for Circuit Analysis. Micromachines, 14(2), 265,1- 18. (SCIE)
  13. Chia-Chi Fang, Ping-Feng Pai*, Chi-Ju Lai, Ying-Lei Lin (2022, Dec). Using light
    gradient boosting machine with genetic algorithms and google trends in forecasting
    COVID-19 confirmed cases. International Journal of Information and Management
    Sciences, 33(4), 353-367. (EI)
  14. Guo-Yu Huang, Chi-Ju Lai, Ping-Feng Pai* (2022, Oct). Forecasting hourly
    intermittent rainfall by deep belief networks with simple exponential smoothing.
    Water Resources Management, 36(13), 5207–5223. (SCIE)
  15. Ying-Lei Lin, Chi-Ju Lai, Ping-Feng Pai* (2022, Oct). Using Deep Learning
    Techniques in Forecasting Stock Markets by Hybrid Data with Multilingual Sentiment
    Analysis. Electronics, 11(21),3513,1-19. (SCIE)
  16. Jung-Pin Lai, Ying-Lei Lin, Ho-Chuan Lin, Chih-Yuan Shih, Yu-Po Wang, Ping- Feng
    Pai* (2022, Aug). RLC Circuit Forecast in Analog IC Packaging and Testing by
    Machine Learning Techniques. Micromachines, 13(8),1305,1-13.(SCIE)
  17. Yu-Ming Chang, Chieh-Huang Chen, Jung-Pin Lai, Ying-Lei Lin , Ping-Feng Pai*
    (2021, Nov). Forecasting Hotel Room Occupancy Using Long Short-Term Memory
    Networks with Sentiment Analysis and Scores of Customer Online Reviews. Applied
    Sciences, 11(21), 10291, 1-14. (SCIE)
  18. Jung-Pin Lai, Yu-Ming Chang, Chieh-Huang Chen, Ping-Feng Pai* (2020, Aug). A
    Survey of Machine Learning Models in Renewable Energy Predictions. Applied
    Sciences, 10(17), 5975,1-20. (SCIE)
  19. Ping-Feng Pai*, Wen-Chang Wang (2020, Aug). Using Machine Learning Models and Actual Transaction Data for Predicting Real Estate Prices. Applied Sciences, 10(17), 5832, 1-11. (SCIE)
  20. Yi-Ting Huang, Ping-Feng Pai* (2020, Apr). Using the least squares support vector
    regression to forecast movie sales by data from Twitter and movie databases.
    Symmetry, 12(4), 625,1-10. (SCIE)
  21. Kuo-Ping Lin, Ping-Feng Pai*, Yi-Ju Ting (2019, Jul). Deep belief networks with
    genetic algorithms in forecasting wind speed. IEEE Access, 7, 99244-99253. (SCIE)
  22. Ping-Feng Pai*, Chia-Hsin Liu (2018, Oct). Predicting vehicle sales by sentiment
    analysis of Twitter data and stock market values. IEEE Access, 6,57655-57662.
    (SCIE).
  23. Ping-Feng Pai*, Ling-Chuang Hong, Kuo-Ping Lin (2018, Jul). Using Internet search trends and historical trading data for predicting stock markets by the least squares support vector regression model. Computational Intelligence and Neuroscience, Volume 2018, Article ID 6305246, 15 pages. (SCIE)
  24. Kuo-Ping Lin, Ming-Lang Tseng, Ping-Feng Pai (2018, Jan). Sustainable supply hain
    management using approximate fuzzy DEMATEL method. Resources, Conservation
    and Recycling, 128,134-142. (SCIE)