KIEE - The Transactions of the Korean Institute of Electrical Engineers

1

M. Xie, 2019, Development of Artificial Intelligence and Effects on Financial System, Journal of Physics: Conference Series, Vol. 1187, No. 3, pp. 032084

2

T. Chen, C. Guestrin, 2016, XGBoost: a Scalable Tree Boosting System, pp. 785-794

3

Y. Yang, C. H. Liu, S. Chen, 2014, Stock market prediction based on SVM optimized by genetic algorithm, Procedia Computer Science, Vol. 31, pp. 1130-1135

4

T. Fischer, C. Krauss, 2018, Deep learning with long short-term memory networks for financial market predictions, European Journal of Operational Research, Vol. 270, No. 2, pp. 654-69

5

W. Bao, J. Yue, Y. Rao, 2017, A deep learning framework for financial time series using stacked autoencoders and long-short term memory, PLOS ONE, Vol. 12, No. 7, pp. e0180944

6

Y. Bao, Z. Yue, Y. Rao, 2019, A deep learning framework for financial time series using stacked LSTM, Procedia Computer Science, Vol. 147, pp. 632-638

7

X. Ding, Y. Zhang, T. Liu, J. Duan, 2016, Knowledge-Driven Event Embedding for Stock Prediction, pp. 2133-2142

8

C. Krauss, X. A. Do, N. Huck, 2017, Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500, European Journal of Operational Research, Vol. 259, No. 2, pp. 689-702

9

G. E. P. Box, G. M. Jenkins, G. C. Reinsel, G. M. Ljung, 2015, Time Series Analysis: Forecasting and Control

10

O. Shobayo, S. Adeyemi-Longe, O. Popoola, O. Okoyeigbo, 2025, A Comparative Analysis of Machine Learning and Deep Learning Techniques for Accurate Market Price Forecasting, Analytics, Vol. 4, No. 1, pp. 5

11

M. Ballings, D. Van den Poel, N. Hespeels, R. Gryp, 2015, Evaluating multiple classifiers for stock price direction prediction, Expert Systems with Applications, Vol. 42, No. 20, pp. 7046-56

12

E. Chong, C. Han, F. C. Park, 2017, Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies, Expert Systems with Applications, Vol. 83, pp. 187-205

13

J. Patel, S. Shah, P. Thakkar, K. Kotecha, 2015, Predicting stock market index using fusion of machine learning techniques, Expert Systems with Applications, Vol. 42, No. 4, pp. 2162-2172

14

L. Zhang, C. Aggarwal, G. J. Qi, 2017, Stock Price Prediction via Discovering Multi-Frequency Trading Patterns, pp. 2141-2149

15

A. Bansal, A. Singh, S. Roy, K. Agarwal, 2024, Price Wise a Deep Learning Approach to Stock Price Prediction, pp. 1-6

16

L. Mochurad, A. Dereviannyi, 2024, An ensemble approach integrating LSTM and ARIMA models for enhanced financial market predictions, Royal Society Open Science, Vol. 11, No. 9, pp. 240699

17

X. Duan, M. Pan, 2024, An intelligent financial data mining system using a fuzzy clustering multimedia approach, Journal of Control and Decision, Vol. 12, No. 4, pp. 1-10

18

Z. Li, J. Wang, 2017, An optimization application of artificial intelligence technology in enterprise financial management, Boletin Tecnico/Technical Bulletin, Vol. 55, No. 11, pp. 83-89

19

D. Jahed Armaghani, E. Tonnizam Mohamad, M. Hajihassani, S. V. Alavi Nezhad Khalil Abad, A. Marto, M. R. Moghaddam, 2015, Evaluation and prediction of flyrock resulting from blasting operations using empirical and computational methods, Engineering with Computers, Vol. 32, No. 1, pp. 109-21

20

X. Gong, Z. Wang, L. Wang, 2018, Research on financial early warning model for papermaking enterprise based on particle swarm K-means algorithm, Paper Asia, Vol. 34, No. 6, pp. 41-45

21

S. Zhai, 2017, Research on enterprise financial management and decision making based on decision tree algorithm, Boletin Tecnico/Technical Bulletin, Vol. 55, No. 15, pp. 166-173

22

L. Wang, Y. Liu, J. Wu, 2018, Research on financial advertisement personalised recommendation method based on customer segmentation, International Journal of Wireless and Mobile Computing, Vol. 14, No. 1, pp. 97

23

H. Sun, Z. Yao, Q. Miao, 2021, Design of Macroeconomic Growth Prediction Algorithm Based on Data Mining, Mobile Information Systems, Vol. 2021, pp. 1-8

24

Y. Kang, 2022, Fusion analysis of management accounting and financial accounting based on data mining, Vol. 12330, pp. 375-380

25

D. Koishiyeva, A. Bissembayev, T. Iliev, J. W. Kang, A. Mukasheva, 2024, Classification of Skin Lesions using PyQt5 and Deep Learning Methods, pp. 1-7

26

S. Lessmann, B. Baesens, H. V. Seow, L. C. Thomas, 2015, Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research, European Journal of Operational Research, Vol. 247, No. 1, pp. 124-36

27

W. Jin, N. Wang, L. Zhang, X. Tian, B. Shi, B. Zhao, 2025, A Review of AI-Driven Automation Technologies: Latest Taxonomies, Existing Challenges, and Future Prospects, Computers, Materials and Continua, Vol. 84, No. 3, pp. 3961-4018

28

A. Tolkynbekova, D. Koishiyeva, A. Bissembayev, D. Mukhammejanova, A. Mukasheva, J. W. Kang, 2025, Comparative Analysis of the Predictive Risk Assessment Modeling Technique Using Artificial Intelligence, Journal of Electrical Engineering & Technology, Vol. 20, No. 6, pp. 4509-26

29

O. Bayazov, A. Aidos, J. W. Kang, A. Mukasheva, 2025, Voice Biometric Authentication Using AI: A Comparative Study on Neural Network Robustness to Noise and Spoofing, The Transactions of the Korean Institute of Electrical Engineers, Vol. 74, No. 10, pp. 1731-1739

KIEEThe Transactions of
the Korean Institute of Electrical Engineers

The Transactions of the Korean Institute of Electrical Engineers

ISO Journal TitleTrans. Korean. Inst. Elect. Eng.

Journal Search

Journal XML

References

KIEEThe Transactions ofthe Korean Institute of Electrical Engineers