Skip to menu Skip to content Skip to footer

2024

Journal Article

Probabilistic quantile multiple fourier feature network for lake temperature forecasting: incorporating pinball loss for uncertainty estimation

Liu, Siyuan, Deng, Jiaxin, Yuan, Jin, Li, Weide, Li, Xi'an, Xu, Jing, Zhang, Shaotong, Wu, Jinran and Wang, You-Gan (2024). Probabilistic quantile multiple fourier feature network for lake temperature forecasting: incorporating pinball loss for uncertainty estimation. Earth Science Informatics, 17 (6), 1-14. doi: 10.1007/s12145-024-01448-7

Probabilistic quantile multiple fourier feature network for lake temperature forecasting: incorporating pinball loss for uncertainty estimation

2024

Journal Article

Multiscale-integrated deep learning approaches for short-term load forecasting

Yang, Yang, Gao, Yuchao, Wang, Zijin, Li, Xi’an, Zhou, Hu and Wu, Jinran (2024). Multiscale-integrated deep learning approaches for short-term load forecasting. International Journal of Machine Learning and Cybernetics, 15 (12), 6061-6076. doi: 10.1007/s13042-024-02302-4

Multiscale-integrated deep learning approaches for short-term load forecasting

2024

Journal Article

Assessing and predicting water quality index with key water parameters by machine learning models in coastal cities, China

Xu, Jing, Mo, Yuming, Zhu, Senlin, Wu, Jinran, Jin, Guangqiu, Wang, You-Gan, Ji, Qingfeng and Li, Ling (2024). Assessing and predicting water quality index with key water parameters by machine learning models in coastal cities, China. Heliyon, 10 (13) e33695, 1-19. doi: 10.1016/j.heliyon.2024.e33695

Assessing and predicting water quality index with key water parameters by machine learning models in coastal cities, China

2024

Journal Article

Pinball-Huber boosted extreme learning machine regression: a multiobjective approach to accurate power load forecasting

Yang, Yang, Lou, Hao, Wang, Zijin and Wu, Jinran (2024). Pinball-Huber boosted extreme learning machine regression: a multiobjective approach to accurate power load forecasting. Applied Intelligence, 54 (17-18), 8745-8760. doi: 10.1007/s10489-024-05651-3

Pinball-Huber boosted extreme learning machine regression: a multiobjective approach to accurate power load forecasting

2024

Journal Article

Solving a class of multi-scale elliptic PDEs by Fourier-based mixed physics informed neural networks

Li, Xi'an, Wu, Jinran, Tai, Xin, Xu, Jianhua and Wang, You-Gan (2024). Solving a class of multi-scale elliptic PDEs by Fourier-based mixed physics informed neural networks. Journal of Computational Physics, 508 113012. doi: 10.1016/j.jcp.2024.113012

Solving a class of multi-scale elliptic PDEs by Fourier-based mixed physics informed neural networks

2024

Journal Article

An adaptive trimming approach to Bayesian additive regression trees

Cao, Taoyun, Wu, Jinran and Wang, You-Gan (2024). An adaptive trimming approach to Bayesian additive regression trees. Complex & Intelligent Systems, 10 (5), 1-19. doi: 10.1007/s40747-024-01516-x

An adaptive trimming approach to Bayesian additive regression trees

2024

Journal Article

Probabilistic sunspot predictions with a gated recurrent units-based combined model guided by pinball loss

Cui, Zhesen, Ding, Zhe, Xu, Jing, Zhang, Shaotong, Wu, Jinran and Lian, Wei (2024). Probabilistic sunspot predictions with a gated recurrent units-based combined model guided by pinball loss. Scientific Reports, 14 (1) 13601, 13601. doi: 10.1038/s41598-024-63878-z

Probabilistic sunspot predictions with a gated recurrent units-based combined model guided by pinball loss

2024

Journal Article

Item response theory models for polytomous multidimensional forced‐choice items to measure construct differentiation

Qiu, Xuelan, de la Torre, Jimmy, Wang, You‐Gan and Wu, Jinran (2024). Item response theory models for polytomous multidimensional forced‐choice items to measure construct differentiation. Educational Measurement: Issues and Practice, 43 (4), 157-168. doi: 10.1111/emip.12621

Item response theory models for polytomous multidimensional forced‐choice items to measure construct differentiation

2024

Journal Article

Augmented support vector regression with an autoregressive process via an iterative procedure

Wu, Jinran, Wang, You-Gan and Zhang, Hao (2024). Augmented support vector regression with an autoregressive process via an iterative procedure. Applied Soft Computing, 158 111549, 1-13. doi: 10.1016/j.asoc.2024.111549

Augmented support vector regression with an autoregressive process via an iterative procedure

2024

Journal Article

A survey on wind power forecasting with machine learning approaches

Yang, Yang, Lou, Hao, Wu, Jinran, Zhang, Shaotong and Gao, Shangce (2024). A survey on wind power forecasting with machine learning approaches. Neural Computing and Applications, 36 (21), 12753-12773. doi: 10.1007/s00521-024-09923-4

A survey on wind power forecasting with machine learning approaches

2024

Journal Article

Foreword: Machine learning in environmental modelling

Wang, You-Gan and Wu, Jinran (2024). Foreword: Machine learning in environmental modelling. Environmental Modeling and Assessment, 29 (3), 425-426. doi: 10.1007/s10666-024-09981-x

Foreword: Machine learning in environmental modelling

2024

Journal Article

Interaction between internal solitary waves and the seafloor in the deep sea

Tian, Zhuangcai, Huang, Jinjian, Xiang, Jiaming, Zhang, Shaotong, Wu, Jinran, Liu, Xiaolei, Luo, Tingting and Yue, Jianhua (2024). Interaction between internal solitary waves and the seafloor in the deep sea. Deep Underground Science and Engineering, 3 (2), 149-162. doi: 10.1002/dug2.12095

Interaction between internal solitary waves and the seafloor in the deep sea

2024

Journal Article

Optimization of suspended particulate transport parameters from measured concentration profiles with a new analytical model

Zhang, Shaotong, Zhao, Zixi, Wu, Jinran, Perrochet, Pierre, Wang, You-Gan, Li, Guangxue and Li, Sanzhong (2024). Optimization of suspended particulate transport parameters from measured concentration profiles with a new analytical model. Water Research, 254 121407, 121407. doi: 10.1016/j.watres.2024.121407

Optimization of suspended particulate transport parameters from measured concentration profiles with a new analytical model

2024

Journal Article

Rapeseed seed coat color classification based on the visibility graph algorithm and hyperspectral technique

Zou, Chaojun, Zhu, Xinghui, Wang, Fang, Wu, Jinran and Wang, You-Gan (2024). Rapeseed seed coat color classification based on the visibility graph algorithm and hyperspectral technique. Agronomy, 14 (5) 941, 941. doi: 10.3390/agronomy14050941

Rapeseed seed coat color classification based on the visibility graph algorithm and hyperspectral technique

2024

Journal Article

Physical informed neural networks with soft and hard boundary constraints for solving advection-diffusion equations using Fourier expansions

Li, Xi'an, Deng, Jiaxin, Wu, Jinran, Zhang, Shaotong, Li, Weide and Wang, You-Gan (2024). Physical informed neural networks with soft and hard boundary constraints for solving advection-diffusion equations using Fourier expansions. Computers and Mathematics with Applications, 159, 60-75. doi: 10.1016/j.camwa.2024.01.021

Physical informed neural networks with soft and hard boundary constraints for solving advection-diffusion equations using Fourier expansions

2024

Journal Article

Estimation of sediment transport parameters from measured suspended concentration time series under waves and currents with a new conceptual model

Zhang, Shaotong, Zhao, Zixi, Li, Guangxue, Wu, Jinran, Wang, You-Gan, Nielsen, Peter, Jeng, Dong-Sheng, Qiao, Lulu, Wang, Chenghao and Li, Sanzhong (2024). Estimation of sediment transport parameters from measured suspended concentration time series under waves and currents with a new conceptual model. Water Resources Research, 60 (4) e2023WR034933, 1-20. doi: 10.1029/2023WR034933

Estimation of sediment transport parameters from measured suspended concentration time series under waves and currents with a new conceptual model

2024

Journal Article

Robust augmented estimation for hourly PM 2.5 using heteroscedastic spatiotemporal models

Song, Yanan, Wu, Jinran, Fu, Liya and Wang, You-Gan (2024). Robust augmented estimation for hourly PM 2.5 using heteroscedastic spatiotemporal models. Stochastic Environmental Research and Risk Assessment, 38 (4), 1423-1451. doi: 10.1007/s00477-023-02628-5

Robust augmented estimation for hourly PM 2.5 using heteroscedastic spatiotemporal models

2024

Journal Article

Inflation transmission diagnostics via a Bayesian graph vector autoregressive model with Markov switching

Fu, Jiali, Cai, Fengjing, Wu, Jinran, Zhao, Shangrui and Wang, You-Gan (2024). Inflation transmission diagnostics via a Bayesian graph vector autoregressive model with Markov switching. Journal of Systems Science and Complexity, 38 (4), 1659-1682. doi: 10.1007/s11424-024-3022-6

Inflation transmission diagnostics via a Bayesian graph vector autoregressive model with Markov switching

2024

Journal Article

Solving the one dimensional vertical suspended sediment mixing equation with arbitrary eddy diffusivity profiles using temporal normalized physics-informed neural networks

Zhang, Shaotong, Deng, Jiaxin, Li, Xi'an, Zhao, Zixi, Wu, Jinran, Li, Weide, Wang, You-Gan and Jeng, Dong-Sheng (2024). Solving the one dimensional vertical suspended sediment mixing equation with arbitrary eddy diffusivity profiles using temporal normalized physics-informed neural networks. Physics of Fluids, 36 (1) 017132. doi: 10.1063/5.0179223

Solving the one dimensional vertical suspended sediment mixing equation with arbitrary eddy diffusivity profiles using temporal normalized physics-informed neural networks

2024

Book Chapter

Recent advances in longitudinal data analysis

Fu, Liya, Wang, You-Gan and Wu, Jinran (2024). Recent advances in longitudinal data analysis. Handbook of statistics: modeling and analysis of longitudinal data. (pp. 173-221) edited by Donald E.K. Martin, Arni S.R. Srinivasa Rao and C.R. Rao. Amsterdam, Netherlands: Elsevier. doi: 10.1016/bs.host.2023.10.007

Recent advances in longitudinal data analysis