基本信息：
王兆才，男，籍贯山东潍坊，博士，副教授，硕士生导师。手机：15692166813，Email：zcwang@shou.edu.cn; zcwang1028@163.com. ORCID：0000-0003-1396-6835.
教育与工作经历：
2006年7月-今 上海海洋大学 beat365官方最新版
2016年9月-2017年8月 北京大学 信息科学技术学院 访问学者
2009年9月-2012年6月 复旦大学 计量经济学 博士
2003年9月-2006年3月 上海交通大学 计算数学硕士
教学工作：
微课比赛华东赛区二等奖，共同主讲课程获得国家级一流课程、上海市一流课程、上海市优质在线课程、上海海洋大学精品课程等称号。
学生工作：
指导学生获得全国大学生数学建模二等奖，上海市数学建模一等奖等多项，获得上海市优秀数学建模指导老师，获上海海洋大学育才奖等荣誉，指导本科生发表中科院1区Top论文多篇，指导研究生均位列学院前5%和获得国家奖学金，上海市优秀毕业生称号，。
科研研究方向：
1. 水文预报；2. 梯级水库调度；3. 水-能-粮-碳耦合系统
发表科研论文：
第一或通讯发表相关SCI论文80余篇（包括《Journal of Cleaner Production》，《Science of the Total Environment》，《Water Resources Research》，《Journal of Environmental Management》，《Journal of Hydrology》等中科院1区Top期刊论文20余篇），ESI热点论文4篇，ESI高被引10篇，发明专利4项，H-index：22。其中近3年第一或通讯发表的36篇SCI论文及《水利学报》篇如下：
[1] Huang, J., Wang, Z.*, Dong, J., & Wu, J. (2024). Research on runoff interval prediction method based on deep learning ensemble modeling with hydrological factors. Stochastic Environmental Research and Risk Assessment, Accepted. doi: 10.1007/s00477-024-02780-6 (IF：3.9，JCR1区)
[2] Yao, Z., Wang, Z.*, Huang, J., Xu, N., Cui, X., & Wu, J. (2024). Interpretable prediction, classification and regulation of water quality: A case study of Poyang Lake, China. Science of the Total Environment, 951,175407. (Top期刊，IF：8.2，JCR1区)
[3] Li, Y., Wang, Z.*, & Liu, S. (2024). Enhance carbon emission prediction using bidirectional long short-term memory model based on text-based and data-driven multimodal information fusion. Journal of Cleaner Production, 471, 143301. (Top期刊，IF：9.7，JCR1区)
[4] Chen, L., Wang, Z.*, Jiang, Z., & Lin, X. (2024). Deep learning models for multi-step prediction of water levels incorporating meteorological variables and historical data. Stochastic Environmental Research and Risk Assessment, Accepted. doi: 10.1007/s00477-024-02766-4 (IF：3.9，JCR1区)
[5] Wang, Z., Xu, N., Bao, X., Wu, J., & Cui, X. (2024). Spatio-temporal Deep Learning Model for Accurate Streamflow Prediction with Multi-source Data Fusion. Environmental Modelling & Software, 178, 106091. (IF：4.8，JCR1区)
[6] Wu, J., Wang, Z.*, Dong, J., *Yao, Z., Chen, X., Li, Q., & Fan, H. (2024). Multi-step ahead dissolved oxygen concentration prediction based on knowledge guided ensemble learning and explainable artificial intelligence. Journal of Hydrology, 636, 131297. (Top期刊，IF：5.9，JCR1区)
[7] Wang, Z., Wu, X., Liang, K., & Wu, T. (2024). Exploring the Potential of DNA Computing for Complex Big Data Problems: A Case Study on the Traveling Car Renter Problem. IEEE Transactions on Nanobioscience, 23(3), 391-402. (IF：3.7，JCR1区)
[8] Wu, J., Chen, X., Li, R., Wang, A., Huang, S., Li, Q., Qi, H., Liu, M., Cheng, H., & Wang, Z.* (2024). A novel framework for high resolution air quality index prediction with interpretable artificial intelligence and uncertainties estimation. Journal of Environmental Management, 357, 120785. (Top期刊，IF：8，JCR1区)
[9] Song, Q., Wang, Z.*, & Wu, T. (2024). Risk analysis and assessment of water resource carrying capacity based on weighted gray model with improved entropy weighting method in the central plains region of China. Ecological Indicators, 160, 111907. (Top期刊，IF：7，JCR1区)
[10] Yang, Z., Wang, Z.*, Yao, Z., & Bao, X. (2024). Optimal allocation planning of regional water resources with multiple objectives using improved firefly algorithm. AQUA—Water Infrastructure, Ecosystems and Society, 73(4), 746-770. (IF：2.1，JCR2区)
[11] Cui, X., Wang, Z.*, Xu, N., Wu, J., & Yao, Z. (2024). A secondary modal decomposition ensemble deep learning model for groundwater level prediction using multi-data. Environmental Modelling & Software, 175,105969. (IF：4.8，JCR1区)
[12] Dong, J., Wang, Z.*, Wu, J., Cui, X., & Pei, R. (2024), A Novel Runoff Prediction Model Based on Support Vector Machine and Gate Recurrent unit with Secondary Mode Decomposition. Water Resources Management, 38(3), 1655-1674. (IF：3.9，JCR1区)
[13] Wang, Z., Zhao, H., Bao, X., & Wu, T. (2024), Multi-objective optimal allocation of water resources based on improved marine predator algorithm and entropy weighting method. Earth Science Informatics, 17(2), 1483-1499. (IF：2.7，JCR2区)
[14] Wang, Z., Wang, Q., Liu, Z., & Wu, T. (2024), A deep learning interpretable model for river dissolved oxygen multi-step and interval prediction based on multi-source data fusion. Journal of hydrology, 629, 130637. (Top期刊，IF：5.9，JCR1区)
[15] Dong, J., Wang, Z.*, Wu, J., Huang, J., & Zhang, C. (2023), A water quality prediction model based on signal decomposition and ensemble deep learning techniques. Water Science and Technology, 88(10), 2611-2632. (IF：2.5，JCR2区)
[16] Zhang, C., Zou, Z., Wang, Z.*, & Wang, J. (2023), Ensemble deep learning modeling for Chlorophyll-a concentration prediction based on two-layer decomposition and attention mechanisms. Acta Geophysica, Accepted. DOI: 10.1007/s11600-023-01240-z (IF：2，JCR2区)
[17] Wu, J., Wang, Z.*, Dong, J., Cui, X., Tao, S., & Chen, X. (2023), Robust Runoff Prediction with Explainable Artificial Intelligence and Meteorological Variables from Deep Learning Ensemble Model. Water Resources Research, 59(9), e2023WR035676. (Top期刊，IF：4.6，JCR1区)
[18] Yao, Z., Wang, Z.*, Wu, T., & Lu, W. (2024), A hybrid data-driven deep learning prediction framework for lake water level based on the fusion of meteorological and hydrological multi-source data. Natural Resources Research, 33, 163-190. (IF：4.8，JCR1区)
[19] Wang, Z., Liang, K., Bao, X., & Wu, T. (2024), A novel Algorithm for Solving the Prize Collecting Traveling Salesman Problem based on DNA Computing, IEEE Transactions on Nanobioscience, 23(2), 220-232. (IF：3.7，JCR1区)
[20] Yao, Z., Wang, Z.*, Wang, D., Wu, J., & Chen, L. (2023), An ensemble CNN-LSTM and GRU adaptive weighting model based improved sparrow search algorithm for predicting runoff using historical meteorological and runoff data as input. Journal of hydrology, 625, 129977. (Top期刊，IF：5.9，JCR1区)
[21] Wang, Z., Liang, K., Bao, X., & Wu, T. (2023). Quantum speedup for solving the minimum vertex cover problem based on Grover search algorithm. Quantum Information Processing, 22(7), 271. (IF：2.2，JCR1区)
[22] Bao, X., Wang, G., Xu, L., & Wang, Z.* (2023). Solving the Min-Max Clustered Traveling Salesmen Problem Based on Genetic Algorithm. Biomimetics, 8(2), 238. (IF：3.4，JCR1区)
[23] Wang, Z., Wang, Q., & Wu, T.# (2023). A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM, Frontiers of Environmental Science & Engineering, 17(7), 88. (IF：6.1，JCR1区)
[24] Yao, Z., Wang, Z.*, Cui, X., & Zhao, H. (2023). Research on multi-objective optimal allocation of regional water resources based on improved sparrow search algorithm. Journal of Hydroinformatics, 25(4), 1413-1437. (IF：2.2，JCR2区)
[25] Tan, R., Hu, Y., Wang, Z.* (2023), A multi-source data-driven model of lake water level based on variational modal decomposition and external factors with optimized bi-directional long short-term memory neural network, Environmental Modelling & Software, 167, 105766. (IF：4.8，JCR1区)
[26] Tan, R., Wang, Z.*, Wu, T., Wu, J. (2023), A data-driven model for water quality prediction in Tai Lake, China, using secondary modal decomposition with multidimensional external features, Journal of Hydrology-Region study, 47, 101435. (IF：4.7，JCR1区)
[27] Wu, J., Dong, J., Wang, Z.*, Hu, Y., & Dou, W. (2023). A novel hybrid model based on deep learning and error correction for crude oil futures prices forecast. Resources Policy, 83, 103602. (Top期刊)
[28] Cui, X., Wang, Z.*, & Pei, R. (2023). A VMD-MSMA-LSTM-ARIMA model for precipitation prediction. Hydrological Sciences Journal, 68(6), 810-839. (IF：2.8，JCR2区)
[29] Wu, J., Wang, Z.*, Hu, Y., Tao, S. & Dong, J. (2023). Runoff Forecasting using Convolutional Neural Networks and optimized Bi-directional Long Short-term Memory, Water Resources Management, 37 (2), 937-953. (IF：3.9，JCR1区)
[30] Chen, L., Wu, T., Wang, Z.*, Lin, X., & Cai, Y. (2023). A novel hybrid BPNN model based on adaptive evolutionary Artificial Bee Colony Algorithm for water quality index prediction. Ecological Indicators, 146, 109882. (Top期刊，ESI高被引，IF：7，JCR1区)
[31] Wang, Z., Deng, A., Wang, D., & Wu, T. (2022). A parallel algorithm to solve the multiple travelling salesmen problem based on molecular computing model. International Journal of Bio-Inspired Computation, 20(3), 160-171. (IF：1.7，JCR2区)
[32] Wang, Z., Wu, X., & Wu, T. (2022). A Parallel DNA Algorithm for Solving the Quota Traveling Salesman Problem Based on Biocomputing Model, Computational Intelligence and Neuroscience, 2022, 1450756. (IF：3.1，JCR2区)
[33] Wu, J., & Wang, Z.* (2022). A hybrid model for water quality prediction based on an artificial neural network, wavelet transform, and long short-term memory. Water, 14(4), 610. (IF：3，JCR2区)
[34] Wu, X., Wang, Z.*, Wu, T., & Bao, X. (2022). Solving the Family Traveling Salesperson Problem in the Adleman–Lipton Model Based on DNA Computing. IEEE Transactions on NanoBioscience, 21(1), 75-85. (IF：3.7，JCR1区)
[35] Wu, X., & Wang, Z.* (2022). Multi-objective optimal allocation of regional water resources based on slime mould algorithm. The Journal of Supercomputing, 78 (16), 18288-18317. (IF：2.5，JCR2区)
[36] Guo, N., & Wang, Z.* (2022). A combined model based on sparrow search optimized BP neural network and Markov chain for precipitation prediction in Zhengzhou City, China. Journal of Water Supply: Research and Technology - AQUA, 71(6), 782-800. (IF：4.3，JCR1区)
[37] 黄靖涵，王兆才*，吴俊豪，姚之远，基于深度学习集合优化模型的径流区间预测研究，水利学报。接受日期：2024-7-29
科研项目：
主持省部级以上科研项目十余项，包括：
（1）中国教育部人文社会科学研究基金规划项目，长江上游水文预报与梯级水库群调度耦合系统的动态多目标优化机制研究，2024/10-2026/9，主持
（2）中国水利水电科学研究院泥沙科学与北方河流治理重点实验室开放研究基金，梯级水库群多目标联合调度的算法研究，2024/1-2025/12，主持；
（3）水能资源利用关键技术湖南省重点实验室开放研究基金面上项目，金沙江段梯级水库群多目标联合调度，2024/1-2025/12，主持；
（4）中国水利水电科学研究院流域水循环模拟与调控国家重点实验室开放研究基金，基于自组装纳米金DNA计算的流域水沙优化配置算法研究，2019/05-2021/04，已结题（评价等级：A），主持；
（5）中国水利水电科学研究院流域水循环模拟与调控国家重点实验室开放基金， 基于生物编码结构的水沙动力学并行计算算法研究，2016/05-2018/04，已结题（评价等级：A），主持。
（6）上海市高校青年骨干教师国内访问学者人才计划，高性能并行计算算法研究，2016/09-2017/06，已结题，主持；
社会工作：
《Water》期刊特刊编辑，《Applied Computational Intelligence and Soft Computing》期刊编辑，以及《River》，《华北水利水电大学学报》和《水利水电技术》青年编委。
