[1]Chaodong Fan, Shanghao Nie, Leyi Xiao*, Lingzhi Yi, Gongrong Li. Short-term industrial load forecasting based on error correction and hybridensemble learning [J]. Energy & Buildings, 2024, 313: 114261 (SCI, IF=6.6, JCR一区)

[2]Chaodong Fan, Shanghao Nie, Leyi Xiao*, Lingzhi Yi, Yuetang Wu, Gongrong Li. A multi-stage ensemble model for power load forecasting based on decomposition, error factors, and multi-objective optimization algorithm [J]. International Journal of Electrical Power & Energy Systems. 2023.11.(SCI, IF=5.2,JCR一区)

[3]Chaodong Fan, Zhenhuan Zeng, Leyi Xiao∗, et al. GFNet: Automatic segmentation of COVID-19 lung infection regions using CT images based on boundary features [J]. Pattern Recognition，2022，DOI：10.1016/j.patcog.2022.108963. (SCI, IF=7.74, JCR一区)

[4]Chaodong Fan, Jiawei Wang, Leyi Xiao*, et al. A coevolution algorithm based on two-staged strategy for constrained multi-objective problems [J]. Applied Intelligence, 2022, https://doi.org/10.1007/s10489-022-03421-7. (SCI, IF=5.086 , JCR一区)

[5]Chaodong Fan, Yunfan Li, Lingzhi Yi, et al. Multi-objective LSTM ensemble model for household short-term load forecasting [J]. Memetic Computing, 2022, 72(1): 1-18. (SCI, IF= 5.900, JCR一区)

[6]Chaodong Fan, Changkun Ding, Leyi Xiao*，et al. Deep belief ensemble network based on MOEA/D for short-term load forecasting [J]. Nonlinear Dynamics, 2021, Vol. 105, 2045-2430. (SCI，IF=5.022，JCR一区，Top期刊)

[7]Chaodong Fan, Bo Hou, Jinhua Zheng, Leyi Xiao*, Lingzhi Yi. A surrogate-assisted particle swarm optimization using ensemble learning for expensive problems with small sample datasets [J]. Applied Soft Computing, 2020, Vol. 91:106242. (SCI, IF: 6.725, JCR一区, Top期刊)

[8]Chaodong Fan, Changkun Ding, Jinhua Zheng, Leyi Xiao, Zhaoyang Ai. Empirical mode decomposition based multi-objective deep belief network for short-term power load forecasting [J]. Neurocomputing, 2020, Vol. 338(C): 110-123. (SCI, IF: 5.719, JCR一区，Top期刊)

[9]Chaodong Fan,Honglin Ouyang, Yingjie Zhang*, Leyi Xiao. Optimal multilevel thresholding using molecular kinetic theory optimization algorithm [J]. Applied Mathematics and Computation, 2014, Vol. 239(15): 391-408. (SCI, IF:4.091, JCR一区, Top期刊)

[10]Chaodong Fan, Ningjun Zheng, Jinhua Zheng, Leyi Xiao, Yingnan Liu. Kinetic-molecular theory optimization algorithm using opposition based learning and varying accelerated motion [J]. Soft Computing, 2020, Vol. 24: 12709-12730. (SCI, IF: 3.643, JCR二区)

[11]Chaodong Fan, Jie Li, Lingzhi Yi, et al. An optimal algorithm based on kinetic-molecular theory with artificial memory to solving economic dispatch problem [J]. Current Science, 2018, Vol. 115(3): 454-464. (SCI, IF: 1.102 , JCR二区)

[12]FAN Chao-dong, REN Ke, ZHANG Ying-jie, YI Ling-zhi*. Optimal multilevel thresholding based on molecular kinetic theory optimization algorithm and line intercept histogram [J]. Journal of Central South University, 2016, Vol. 23(4): 880-890. (SCI, IF: 1.716, JCR二区)

[13]FAN Chao-dong, OUYANG Hong-lin, ZHANG Ying-jie*, AI Zhao-yang. Optimization algorithm based on kinetic-molecular theory [J]. Journal of Central South University, 2013, Vol. 20(12): 3504-3512. (SCI, IF: 1.716, JCR二区)

[14]范朝冬，章兢，易灵芝*. M-精英协同进化分子动理论优化算法[J].通信学报, 2015, Vol. 36(7): 144-152. (EI国内权威期刊)

[15]范朝冬,欧阳红林,张英杰*.基于小概率策略的Otsu图像分割方法[J].电子与信息学报, 2013, Vol. 35 (9): 2081-2087. (EI国内权威期刊)

[16]范朝冬*,欧阳红林,肖乐意.基于空间截面投影的Otsu图像分割算法[J].通信学报, 2014, Vol. 35(5): 70-78. (EI国内权威期刊)

[17]范朝冬,张英杰*,欧阳红林,肖乐意.基于改进斜分Otsu法的回转窑火焰图像分割[J].自动化学报，2014, Vol. 40(11): 2480-2489. (EI国内权威期刊)

[18]范朝冬,刘颖南,章兢,等.弱连接多子群分子动理论优化算法[J].控制理论与应用, 2019, Vol.36(1): 108–119. (EI国内权威期刊)

[19]Chaodong Fan, Ningjun Zheng, Leyi Xiao, Juan Zou. MR brain image segmentation using elite kinetic-molecular theory optimization algorithm [J]. International Journal of Automation and Control, 2020, Vol.14(5/6):593-605 (EI期刊)