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Published: Jan 10, 2024
DOI: 10.4018/IJDWM.336286
Volume 20
Feiqi Liu, Dong Yang, Yuyang Zhang, Chengcai Yang, Jingjing Yang
The rabbit breeding industry exhibits vast economic potential and growth opportunities. Nevertheless, the ineffective prediction of environmental conditions in rabbit houses often leads to the... Show More
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Liu, Feiqi, et al. "Research on Multi-Parameter Prediction of Rabbit Housing Environment Based on Transformer." IJDWM vol.20, no.1 2024: pp.1-19. http://doi.org/10.4018/IJDWM.336286

APA

Liu, F., Yang, D., Zhang, Y., Yang, C., & Yang, J. (2024). Research on Multi-Parameter Prediction of Rabbit Housing Environment Based on Transformer. International Journal of Data Warehousing and Mining (IJDWM), 20(1), 1-19. http://doi.org/10.4018/IJDWM.336286

Chicago

Liu, Feiqi, et al. "Research on Multi-Parameter Prediction of Rabbit Housing Environment Based on Transformer," International Journal of Data Warehousing and Mining (IJDWM) 20, no.1: 1-19. http://doi.org/10.4018/IJDWM.336286

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Published: Feb 20, 2024
DOI: 10.4018/IJDWM.338912
Volume 20
Qiliang Zhu, Changsheng Wang, Wenchao Jin, Jianxun Ren, Xueting Yu
In recent years, deep learning has been widely used as an efficient prediction algorithm. However, this algorithm has strict requirements on the size of training samples. If there are not enough... Show More
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Zhu, Qiliang, et al. "Deep Transfer Learning Based on LSTM Model for Reservoir Flood Forecasting." IJDWM vol.20, no.1 2024: pp.1-17. http://doi.org/10.4018/IJDWM.338912

APA

Zhu, Q., Wang, C., Jin, W., Ren, J., & Yu, X. (2024). Deep Transfer Learning Based on LSTM Model for Reservoir Flood Forecasting. International Journal of Data Warehousing and Mining (IJDWM), 20(1), 1-17. http://doi.org/10.4018/IJDWM.338912

Chicago

Zhu, Qiliang, et al. "Deep Transfer Learning Based on LSTM Model for Reservoir Flood Forecasting," International Journal of Data Warehousing and Mining (IJDWM) 20, no.1: 1-17. http://doi.org/10.4018/IJDWM.338912

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Published: Mar 27, 2024
DOI: 10.4018/IJDWM.341268
Volume 20
JianDong He
Uncertain information in the securities market exhibits fuzziness. In this article, expected returns and liquidity are considered as trapezoidal fuzzy numbers. The possibility mean and mean absolute... Show More
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He, JianDong. "A Fuzzy Portfolio Model With Cardinality Constraints Based on Differential Evolution Algorithms." IJDWM vol.20, no.1 2024: pp.1-14. http://doi.org/10.4018/IJDWM.341268

APA

He, J. (2024). A Fuzzy Portfolio Model With Cardinality Constraints Based on Differential Evolution Algorithms. International Journal of Data Warehousing and Mining (IJDWM), 20(1), 1-14. http://doi.org/10.4018/IJDWM.341268

Chicago

He, JianDong. "A Fuzzy Portfolio Model With Cardinality Constraints Based on Differential Evolution Algorithms," International Journal of Data Warehousing and Mining (IJDWM) 20, no.1: 1-14. http://doi.org/10.4018/IJDWM.341268

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Published: May 29, 2024
DOI: 10.4018/IJDWM.344415
Volume 20
Tianyan Ding
Accurately identifying rumor information is crucial for efficient information assessment. Pretrained Language Models (PLMs) are trained on large text data, understanding and generating human-like... Show More
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Ding, Tianyan. "A Rumors Detection Method Using T5-Based Prompt Learning." IJDWM vol.20, no.1 2024: pp.1-19. http://doi.org/10.4018/IJDWM.344415

APA

Ding, T. (2024). A Rumors Detection Method Using T5-Based Prompt Learning. International Journal of Data Warehousing and Mining (IJDWM), 20(1), 1-19. http://doi.org/10.4018/IJDWM.344415

Chicago

Ding, Tianyan. "A Rumors Detection Method Using T5-Based Prompt Learning," International Journal of Data Warehousing and Mining (IJDWM) 20, no.1: 1-19. http://doi.org/10.4018/IJDWM.344415

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Published: May 7, 2024
DOI: 10.4018/IJDWM.345361
Volume 20
Jayun Yong, Chulyun Kim
The recommender system can be viewed as a matrix completion problem, which aims to predict unknown values within a matrix. Solutions to this problem are categorized into two approaches: transductive... Show More
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Yong, Jayun, and Chulyun Kim. "Hybrid Inductive Graph Method for Matrix Completion." IJDWM vol.20, no.1 2024: pp.1-16. http://doi.org/10.4018/IJDWM.345361

APA

Yong, J. & Kim, C. (2024). Hybrid Inductive Graph Method for Matrix Completion. International Journal of Data Warehousing and Mining (IJDWM), 20(1), 1-16. http://doi.org/10.4018/IJDWM.345361

Chicago

Yong, Jayun, and Chulyun Kim. "Hybrid Inductive Graph Method for Matrix Completion," International Journal of Data Warehousing and Mining (IJDWM) 20, no.1: 1-16. http://doi.org/10.4018/IJDWM.345361

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Published: May 31, 2024
DOI: 10.4018/IJDWM.345406
Volume 20
Meng Huang, Ting Wei
With the development of smart education, gaining insights into students' understanding during the learning process is crucial in teaching. However, traditional knowledge tracking methods face... Show More
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Huang, Meng, and Ting Wei. "GTFN: Knowledge Tracing Model Based on Graph Temporal Fusion Networks." IJDWM vol.20, no.1 2024: pp.1-17. http://doi.org/10.4018/IJDWM.345406

APA

Huang, M. & Wei, T. (2024). GTFN: Knowledge Tracing Model Based on Graph Temporal Fusion Networks. International Journal of Data Warehousing and Mining (IJDWM), 20(1), 1-17. http://doi.org/10.4018/IJDWM.345406

Chicago

Huang, Meng, and Ting Wei. "GTFN: Knowledge Tracing Model Based on Graph Temporal Fusion Networks," International Journal of Data Warehousing and Mining (IJDWM) 20, no.1: 1-17. http://doi.org/10.4018/IJDWM.345406

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All inquiries regarding IJDWM should be directed to the attention of:

Dr. Eric Pardede
Editor-in-Chief
International Journal of Data Warehousing and Mining
La Trobe University, Australia
E-mail: E.Pardede@latrobe.edu.au

Dr. Kiki Adhinugraha
Editor-in-Chief
International Journal of Data Warehousing and Mining
La Trobe University, Australia
E-mail: K.Adhinugraha@latrobe.edu.au

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