[1] L.M. Huang*, Y. Han, W.Y. Duan, Y. Zheng, S. Ma, Ship pitch-roll stabilization by active fins using a controller based on onboard hydrodynamic prediction. Ocean Engineering, 2018, 164:212-227.
[2] L.M. Huang*, Y. Han, W.Y. Duan, Y.S. Chen, S. Ma, Numerical and experimental studies on a predictive control approach for pitch stabilization in heading waves. Ocean Engineering, 2018, 169:388-400.
[3] W.Y. Duan, Y. Han, R.F. Wang, L.M. Huang*. A predictive controller for joint pitch-roll stabilization. Journal of Zhejiang University-SCIENCE A, 2016 (5):399-415.
[4] W.Y. Duan, Y. Han, L.M. Huang, B.B. Zhao*, M.H. Wang. A hybrid EMD-SVR model for the short-term prediction of significant wave height. Ocean Engineering, 2016, 124:54–73.
[5] W.Y. Duan, L.M. Huang*, Y. Han, D.T. Huang. A hybrid EMD-AR model for nonlinear and non-stationary significant wave height forecast. Journal of Zhejiang University-SCIENCE A, 2016(2):115-129.
[6] L.M. Huang*, W.Y. Duan, Y. Han, D.H. Yu, Aladdin. Extending the scope of AR model in forecasting non-stationary ship motion by using AR-EMD technique. Journal of Ship Mechanics, 2015, 19(6):1033-1049.
[7] W.Y. Duan, L.M. Huang*, Y. Han, Y.H. Zhang, S. Huang. Short-term forecast of non-stationary and nonlinear ship motion using an AR-EMD-SVR model. Journal of Zhejiang University-SCIENCE A, 2015(7):562-576.
[8] W.Y. Duan, L.M. Huang*, Y. Han, R. Wang. IRF - AR Model for Short-Term Prediction of Ship Motion. Proceedings of the 25th Annual International Ocean and Polar Engineering Conference. Kona, Hawaii Big Island, USA, 2015, June 21–26.
[9] L.M. Huang*, W.Y. Duan, Y. Han, Y.S. Chen, A review of short-term prediction techniques for ship motions in seaway. Journal of Ship Mechanics, 2014, 18(12) 2014 (12): 1534-1542.
[10] W.Y. Duan, H.S. Zhang, L.M. Huang*. Numerical simulation of trim optimization on resistance performance based on CFD method. Proceedings of the 38th International Conference on Ocean, Offshore and Arctic Engineering. Glasgow, Scotland, UK, 2019, June 09-14.
[11] W.Y. Duan, K. Yang, L.M. Huang*. Numerical Investigations on Sea States Estimation Based on the Convolution Neural Networks Deep Learning Technique. Proceedings of the 29th Annual International Ocean and Polar Engineering Conference. Hawaii Big Island, USA, 2019, June 16-22.
[12] W.Y. Duan, S.L. Duan, L.M. Huang*. A LSTM Deep Learning Model for Deterministic Ship Motions Estimation Using Wave-Excitation Inputs. Proceedings of the 29th Annual International Ocean and Polar Engineering Conference. Hawaii Big Island, USA, 2019, June 16-22.
[13] W.Y. Duan, Z. Shi, L.M. Huang*. Research On The Probability Distribution Of The Underwater Moving Of The Wrecked Target. Proceedings of the 38th International Conference on Ocean, Offshore and Arctic Engineering. Glasgow, Scotland, UK, 2019, June 09-14.
[14] Y.C. Liu*, Q.M. Zheng, W.Y. Duan, L.M. Huang. Improving deterministic pitch motions estimation using bivariate sequential wave input. Proceedings of the 3rd International Conference on Traffic Engineering and Transporation System, 2019.
[15] W.Y. Duan, G.Z. Cao, L.M. Huang*. Ship Maneuvering Prediction Based on CFD Method. The Conference of Japan Society of Naval Architects and Ocean Engineers, Japan, 2019, June 02-05.
[16] Hua Jiang, ShiLiang Duan, Limin Huang*, Yang Han, Heng Yang, Qingwei Ma, Scale effects in AR model real-time ship motion prediction, Ocean Engineering. 2020, 203：1-11.
[17] W.Y. Duan, K. Yang, L.M. Huang*, X.W. Ma. Numerical Investigations on Wave Remote Sensing from Synthetic X-Band Radar Sea Clutter Images by Using Deep Convolutional Neural Networks. Remote Sensing, 2020,169(7):1-21.
[18] Yucheng Liu , Wenyang Duan , Limin Huang *, Shiliang Duan , Xuewen Ma，The input vector space optimization for LSTM deep learning model in real-time prediction of ship motions. Ocean Engineering. 2020, 213:1-10.
[19] Wenyang Duan, Xuewen Ma, Limin Huang*, Shiliang Duan, Yucheng Liu. Phase-resolved wave prediction model for long-crest wave based on machine learning. Computer Methods in Applied Mechanics and Engineering.2020, 372:1-14.
[20] Ma XW, Huang LM*, Duan WY, et al. Experimental investigations on the predictable temporal-spatial zone for the deterministic sea wave prediction of long-crested waves[J]. Journal of Marine Science and Technology, 2021: 1-14.
[21] Duan WY, Shi Z, Yang YM, Huang LM*. Investigations on a moving target's penetration into the seabed sediment using the ALE technique[J]. Ships and Offshore Structures, 2021: 1-13.
[22] 师长, 陈云赛, 黄礼敏*, 段文洋. 失事航天器高速入水砰击数值模拟研究[J]. 华中科技大学学报(自然科学版), 2021, 49(05): 44-49.
[23] 师长, 段文洋, 黄礼敏*, 等. 基于TUMS模型的目标物水下落位散布预测研究[C]. 中国力学大会, 成都, 2021.
[24] 蒋真, 师长，黄礼敏*等. 失事航天器入水砰击荷载特性研究[C]. 中国力学大会, 成都, 2021.
[25] 蒋真, 师长，黄礼敏*等. 失事航天器入水砰击数值模拟与试验研究[C]. 第三十二届全国水动力学研讨会文集, 无锡, 2021.
[26] 景裕，黄礼敏*，张璐，郝伟. 风场时-空分辨率对波浪模式的影响研究[C]. 第三十二届全国水动力学研讨会文集, 无锡, 2021.
[27] 张璐，景裕，邵文勃，段文洋，黄礼敏*.海洋风浪预报与船舶航速优化研究[C]. 第三十二届全国水动力学研讨会文集, 无锡, 2021.
[28] 秦艺超,黄礼敏*,王骁,马学文,段文洋,郝伟.基于人工神经网络的自航浮标测波方法可行性[J/OL].上海交通大学学报:1-8[2022-01-04].DOI:10.16183/j.cnki.jsjtu.2021.094.
[29] 秦艺超，黄礼敏*，马学文，段文洋.船舶类比波浪浮标技术研究进展综述[C].第三十二届全国水动力学研讨会文集, 无锡, 2021.
[30] 郑秋萌，段文洋，黄礼敏*.船舶在波浪中的航向保持性研究[C]. 第三十二届全国水动力学研讨会文集, 无锡, 2021.
[31] 郝伟，黄礼敏*，王晨羽，景裕，马学文.海浪有义波高预报方法对比分析研究[C]. 第三十二届全国水动力学研讨会文集, 无锡, 2021.
[32] Ma X, Huang L*, Duan W, et al. The performance and optimization of ANN-WP model under unknown sea states[J]. Ocean Engineering, 2021, 239: 109858.
[33] Ma XW, Duan WY, Huang LM*, et al. Phase-resolved wave prediction for short crest wave fields using deep learning[J]. Ocean Engineering, 2022, 262: 112170.
[34] Hao W, Wang CY, Chen HY, Huang LM*. A hybrid EMD-LSTM model for non-stationary wave prediction in offshore China[J]. Ocean engineering, 2022,246.
[35] Jing Y, Zhang L, Hao W, Huang LM*. Numerical study of a CNN-based model for regional wave prediction[J]. Ocean engineering, 2022,255.
[36] Duan WY, Yang K, Huang LM*, et al. A DFN-based method for fast prediction of ships' added resistance in heading waves[J]. Ocean Engineering, 2022, 245: 110484.
[37] Yang K, Duan WY, Huang LM*, et al. A prediction method for ship added resistance based on symbiosis of data-driven and physics-based models[J]. Ocean Engineering, 2022, 260: 112012.
[38] Duan WY, Shi Z, Jiang Z, Li HY, Huang LM*. Experimental and numerical investigation of bubble evolution and bubble wall fluctuation mechanism during water entry of flared cavity[J]. Ocean Engineering,2022,266(P5).
[39] Huang LM, Jing Y, Chen HY, Zhang L, Liu YL. A regional wind wave prediction surrogate model based on CNN deep learning network[J]. Applied Ocean Research,2022,126.
[40] Chen HY, Bu YL, Zong K, Huang LM*, Hao W. The Effect of Data Skewness on the LSTM-Based Mooring Load Prediction Model[J]. Journal of Marine Science and Engineering. 2022; 10(12):1931.
[41] Zhang L, Duan WY, Huang LM*, et al. Research on ship speed optimization in ocean routes based on changes in marine environment. ichd2022.
[42] 黄国清*，段文洋，范吉豪，黄礼敏. 潜艇运动生成的德拜磁场模拟仿真[C]. 第三十四届全国水动力学研讨会暨第十七届全国水动力学学术会议论文集, 2023: 1928-1834.
[43] J.H. Fan, W.Y. Duan, L.M. Huang*, L. Zhang, K. Yang. High-fidelity flow field reconstruction model for incompressible fluid with physical constraints[J]. Ocean Engineering, 2023, 280: 114597.
[44] Liu Y, Huang L*, Ma X, et al. A fast, high-precision deep learning model for regional wave prediction[J]. Ocean Engineering, 2023, 288: 115949.
[45] 尧仕杰，段文洋，崔昕邈，黄礼敏*，张璐. 基于多源卫星遥感数据的船舶失事海况特征分析[C]. 第三十四届全国水动力学研讨会暨第十七届全国水动力学学术会议论文集, 2023: 1809-1818.
[46] 崔昕邈，黄礼敏*，尧仕杰，张璐，刘育良. 岛礁海域SWAN模式的源项敏感性分析[C]. 第三十四届全国水动力学研讨会暨第十七届全国水动力学学术会议论文集, 2023: 1791-1799.
[47] Wenyang Duan, Peixin Zhang, Limin Huang*, Ke Yang, Kuo Yang. Ship hull surface reconstruction from scattered points cloud using an RBF neural network mapping technology[J]. Computers & Structures,2023,281: 107012.
[48] Shi Zhang, Duan Wenyang, Huang Zhenhua, Zhang Gen, Jiang Zhen, Huang Limin*. Experimental and numerical investigation on water entry fluctuation effect of flared cavity[J]. Applied Ocean Research, 2023, 135: 103544.
[49] Jiang Zhen, Shi Zhang*, Jiang Hua, Huang Zhenhua, Huang Limin*. Investigation of the load and flow characteristics of variable mass forced sloshing[J]. Physics of Fluids, 2023, 35(3): 033325.
[50] X. Wang, H. Y. Chen, X. W. Ma*, Z. Wang, R. S. Zhou and L.M. Huang *, The Propagation Velocity and Influences of Environmental Factors of Deterministic Sea Wave Prediction in the Long Crest Wave[J]. Journal of Marine Science and Engineering, 2024, 12(4), 633.
[51] H.Y. Chen, L.M. Huang *, X. W. Ma, R. S. Zhou amd S. J. Wang, An Optimization Method of Intelligent Wave Prediction Models in Real Sea Area based on Frequency-band Preprocessing, The 34th International Ocean and Polar Engineering Conference, Rhodes, Greece, June 2024
[52] L. Zhang, W.Y. Duan, X.M. Cui, Y.L. Liu, L.M. Huang*. Surface Current Prediction Based on a Physics-Informed Deep Learning Model[J]. Applied Ocean Research, 2024,148:104005.
[53] Y.L. Liu, L. Zhang *, W. Hao, L. Zhang, L.M. Huang. Predicting temporal and spatial 4-D ocean temperature using satellite data based on a novel deep learning model[J]. Ocean Modelling, 2024, 188: 102333.
[54] K. Zong, Y. L. Liu, S.X. Liu, X. M. Cu, L.M. Huang*. A training strategy for enhancing prediction accuracy of high magnitude oceanic environmental factors based on deep learning model[J]. Ocean Engineering, 2024, 309: 118336.
[55] Lu Zhang, Wenyang Duan, Kedi Wu, Xinmiao Cui, Carlos Guedes Soares, Limin Huang*. Opitimzed WAVEWATCH Ill for Significant Wave Height Computation Using Machine Learning[J]. Ocean Engineering, 2024.
[56] Zhang Shi, Wenyang Duan, Gen Zhang, Jihao Fan, Wei Hao, Limin Huang*. Investigation on the oblique water entry of the flared cavity[J]. Applied Ocean Research, 2024.
