Journal Papers
1. Ge, D. and Zeng, X.J., 2022. Functional fuzzy system: A nonlinear regression model and its learning algorithm for function-on-function regression. IEEE Transactions on Fuzzy Systems, 30(4), pp. 956 – 967.
2. Hu, M., Ge, D., Telford, R., Stephen, B. and Wallom, D.C., 2021. Classification and characterization of intra-day load curves of PV and non-PV households using interpretable feature extraction and feature-based clustering. Sustainable Cities and Society, 75, p.103380.
3. Ge, D. and Zeng, X.J., 2020. Learning data streams online — An evolving fuzzy system approach with self-learning/ adaptive thresholds. Information Sciences, 507, pp.172-184.
4. Ge, D. and Zeng, X.J., 2019. A self-evolving fuzzy system which learns dynamic threshold parameter by itself. IEEE Transactions on Fuzzy Systems, 27(8), pp. 1625 – 1637.
5. Ge, D. and Zeng, X.J., 2018. Learning evolving T–S fuzzy systems with both local and global accuracy–A local online optimization approach. Applied Soft Computing, 68, pp.795-810.
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Book Chapters
1. Ge, D.J. and Zeng, X.J., 2017. Modified evolving participatory learning algorithms for Takagi-Sugeno fuzzy system modelling from streaming data. In Advances in Computational Intelligence Systems (pp. 145-163). Springer, Cham.
Conferences
1. Ge, D. and Zeng, X.J., 2019, Sept. Self-evolving neuro-fuzzy system with applications in high-frequency trading predictions. in International Conference on Fintech & Financial Data Science. (Oral Presentation)
2. Ge, D. and Zeng, X.J., 2017, July. Learning evolving Mamdani fuzzy systems based on parameter optimization. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1-6). IEEE.