I am a research fellow working with Professor Geoffrey J. McLachlan on semi-supervised learning, specifically investigating missingness mechanisms and mixture modelling.
Availability
Dr Jinran Wu is:
Available for supervision
Qualifications
Doctor of Philosophy of Statistics, Queensland University of Technology
A new hybrid model to predict the electrical load in five states of Australia
Wu, Jinran, Cui, Zhesen, Chen, Yanyan, Kong, Demeng and Wang, You-Gan (2019). A new hybrid model to predict the electrical load in five states of Australia. Energy, 166, 598-609. doi: 10.1016/j.energy.2018.10.076
A novel hybrid model based on extreme learning machine, k-nearest neighbor regression and wavelet denoising applied to short-term electric load forecasting
Li, Weide, Kong, Demeng and Wu, Jinran (2017). A novel hybrid model based on extreme learning machine, k-nearest neighbor regression and wavelet denoising applied to short-term electric load forecasting. Energies, 10 (5) 694, 1-16. doi: 10.3390/en10050694
A New Hybrid Model FPA-SVM Considering Cointegration for Particular Matter Concentration Forecasting: A Case Study of Kunming and Yuxi, China
Li, Weide, Kong, Demeng and Wu, Jinran (2017). A New Hybrid Model FPA-SVM Considering Cointegration for Particular Matter Concentration Forecasting: A Case Study of Kunming and Yuxi, China. Computational Intelligence and Neuroscience, 2017 2843651, 1-11. doi: 10.1155/2017/2843651
