系所介紹

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. 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)
  2.  Jung-Pin Lai, Ying-Lei Lin, Yu-Hui Liu*, Ho-Chuan Lin, Chih-Yuan Shih, Yu-Po
    Wang, Ping-Feng Pai (2023, Oct). Machine Learning in Integrated Circuit Substrate
    Electrical Test. 2023 18th International Microsystems, Packaging, Assembly and
    Circuits Technology Conference (IMPACT). (EI)
  3. 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)
  4. 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. (SCIE)
  5. 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)
  6. 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)
  7. 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)
  8. 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)
  9. 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)
  10. 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)
  11. 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)
  12. 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)
  13. 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)
  14. 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)
  15. 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)
  16. 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).
  17. 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.
  18. 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)

 

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