期刊論文

1. 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,
1-14. (SCIE)
2. Jung-Pin Lai, Ying-Lei Lin, Ho-Chuan Lin, Chih-Yuan Shih, Yu-Po Wang, Ping-
Feng Pai* (2023, Jan). Tree-Based Machine Learning Models with Optuna in
Predicting Impedance Values for Circuit Analysis. Micromachines. 14(2),265, 1-18.
(SCIE)
3. 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).
4. Yu-Shan Li, Ping-Feng Pai*, Ying-Lei Lin (2022, Nov). Forecasting inflation rates
by extreme gradient boosting with the genetic algorithm. Journal of Ambient
Intelligence and Humanized Computing. (Accepted). (SCIE).
5. 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).
6. 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)
7. 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(80) 1305,1-13. (SCIE)
8. Chi-Ju Lai, Ping-Feng Pai*, Marvin Marvin, Hsiao-Han Hung, Si-Han Wang and
Din-Nan Chen (2022, Mar). The Use of Convolutional Neural Networks and
Digital Camera Images in Cataract Detection. Electronics, 11(6),887,1-11. (SCIE)
9. 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)
10. 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)
11. 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)
12. 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)
13. 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)
14. 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).
15. 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.
16. Kuo-Ping Lin, Ming-Lang Tseng, Ping-Feng Pai (2018, Jan). Sustainable supply

chain management using approximate fuzzy DEMATEL method. Resources,
Conservation and Recycling, 128,134-142. (SCIE)
17. Ping-Feng Pai*, Lan-Hung ChangLiao, Kuo-Ping Lin (2017, Dec). Analyzing
basketball games by a support vector machines with decision tree model. Neural
Computing & Applications, 28(12),4159–4167. (SCIE)
18. Ping-Feng Pai*, Lei-Chun Chen, Kuo-Ping Lin (2016, Apr). A hybrid data mining
model in analyzing corporate social responsibility. Neural Computing &
Applications, 27(3), 749-760. (SCIE)