Ahmad, A., Xiao, X., Mo, H., & Dong, D. (2025). TFTformer: A novel transformer based model for short-term load forecasting. International Journal of Electrical Power & Energy Systems, 166, 110549. doi: 10.1016/j.ijepes.2025.110549
Journal - Research Article
Surmon, S., Ahmad, A., Xiao, X., & Mo, H. (2024). Comparison of neural network models for short-term load forecasting. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC). (pp. 790-795). IEEE. doi: 10.1109/SMC54092.2024.10831016
Conference Contribution - Published proceedings: Abstract
Chen, P., & Xiao, X. (2024). Novel closed-form point estimators for the beta distribution. Statistical Theory & Related Fields. Advance online publication. doi: 10.1080/24754269.2024.2419360
Journal - Research Article
Ahmad, A., Xiao, X., Mo, H., Li, C., & Dong, D. (2024). Drift-aware dynamic neural network for improving short-term load forecasting. Proceedings of the International Conference on Smart Energy Systems and Technologies (SEST). IEEE. doi: 10.1109/SEST61601.2024.10694209
Conference Contribution - Published proceedings: Full paper
Xiao, X., Ye, Z., & Revie, M. (2024). Learning local cascading failure pattern from massive network failure data. Journal of the Royal Statistical Society: Series C. Advance online publication. doi: 10.1093/jrsssc/qlae030
Journal - Research Article
2025
Journal - Research Article
Ahmad, A., Xiao, X., Mo, H., & Dong, D. (2025). TFTformer: A novel transformer based model for short-term load forecasting. International Journal of Electrical Power & Energy Systems, 166, 110549. doi: 10.1016/j.ijepes.2025.110549
2024
Journal - Research Article
Chen, P., & Xiao, X. (2024). Novel closed-form point estimators for the beta distribution. Statistical Theory & Related Fields. Advance online publication. doi: 10.1080/24754269.2024.2419360
Xiao, X., Ye, Z., & Revie, M. (2024). Learning local cascading failure pattern from massive network failure data. Journal of the Royal Statistical Society: Series C. Advance online publication. doi: 10.1093/jrsssc/qlae030
Mirfin, A., Xiao, X., & Jack, M. W. (2024). TOWST: A physics-informed statistical model for building energy consumption with solar gain. Applied Energy, 369, 123488. doi: 10.1016/j.apenergy.2024.123488
Chen, A. S., Xiao, X., & Yang, D. A. (2024). A Bayesian finite mixture model approach to evaluate dichotomization method for correlated ELISA tests. Preventive Veterinary Medicine, 225, 106144. doi: 10.1016/j.prevetmed.2024.106144
Ahmad, A., Xiao, X., Mo, H., & Dong, D. (2024). Tuning data preprocessing techniques for improved wind speed prediction. Energy Reports, 11, 287-303. doi: 10.1016/j.egyr.2023.11.056
Journal - Research Other
Gao, Z., Xiao, X., Fang, Y.-P., Rao, J., & Mo, H. (2024). A selective review on information criteria in multiple change point detection. Entropy, 26, 50. doi: 10.3390/e26010050
Conference Contribution - Published proceedings: Full paper
Ahmad, A., Xiao, X., Mo, H., Li, C., & Dong, D. (2024). Drift-aware dynamic neural network for improving short-term load forecasting. Proceedings of the International Conference on Smart Energy Systems and Technologies (SEST). IEEE. doi: 10.1109/SEST61601.2024.10694209
Conference Contribution - Published proceedings: Abstract
Surmon, S., Ahmad, A., Xiao, X., & Mo, H. (2024). Comparison of neural network models for short-term load forecasting. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC). (pp. 790-795). IEEE. doi: 10.1109/SMC54092.2024.10831016
2023
Journal - Research Article
Mo, H., Xiao, X., Sansavini, G., & Dong, D. (2023). Optimal defense resource allocation against cyber-attacks in distributed generation systems. Proceedings of the Institution of Mechanical Engineers Part O: Journal of Risk & Reliability. Advance online publication. doi: 10.1177/1748006X231196259
Li, C., & Xiao, X. (2023). On censoring time in statistical monitoring of lifetime data. Technometrics, 65(3), 418-431. doi: 10.1080/00401706.2023.2177351
2022
Journal - Research Article
Khosravi, M., Soleimanmeigouni, I., Ahmadi, A., Nissen, A., & Xiao, X. (2022). Modification of correlation optimized warping method for position alignment of condition measurements of linear assets. Measurement, 201, 111707. doi: 10.1016/j.measurement.2022.111707
Yang, D. A., Xiao, X., Jiang, P., Pfeiffer, D. U., & Laven, R. A. (2022). Keeping continuous diagnostic data continuous: Application of Bayesian latent class models in veterinary research. Preventive Veterinary Medicine, 201, 105596. doi: 10.1016/j.prevetmed.2022.105596
Xiao, X., Mo, H., Zhang, Y., & Shan, G. (2022). Meta-ANN: A dynamic artificial neural network refined by meta-learning for Short-Term Load Forecasting. Energy, 246, 123418. doi: 10.1016/j.energy.2022.123418
Xiao, X., & Li, M. (2022). Fusion of data-driven model and mechanistic model for kiwifruit flesh firmness prediction. Computers & Electronics in Agriculture, 193, 106651. doi: 10.1016/j.compag.2021.106651
Conference Contribution - Published proceedings: Abstract
Mirfin, A., Jack, M., & Xiao, X. (2022). Determining the true value of energy efficiency improvements and demand flexibility services. Proceedings of the 16th Otago Energy Research Centre (OERC) Symposium: An Equitable and Low-Cost Energy Transition. (pp. 30). Retrieved from https://www.otago.ac.nz/oerc/symposia
2021
Journal - Research Article
Tahir, A., Bennin, K. E., Xiao, X., & MacDonell, S. G. (2021). Does class size matter? An in-depth assessment of the effect of class size in software defect prediction. Empirical Software Engineering, 26(5), 106. doi: 10.1007/s10664-021-09991-3
