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.
ORCID：0000-0003-1396-6835.
教育与工作经历：
2006年7月-今 上海海洋大学 信息学院
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
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，指导多名本科生发表中科院1区Top论文，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/通讯作者发表SCI论文100余篇， 其中Top期刊论文30余篇，IF
10的论文10余篇，包括Water Research，Journal of Hydrology(7篇)，Water Resources Research，Applied Energy，Sustainable Cities and Society(2篇)，Agricultural Water Management，Expert Systems with Applications，Journal of Environmental Management，Science of the Total Environment，Journal of Cleaner Production(3篇)，Ecological Indicators(3篇)，IEEE Trans系列(4篇)， Natural Resources Research，Journal of Hydrology: Regional Studies(2篇)， Environmental Modelling & Software(4篇)，Water Resources Management(3篇)，Stochastic Environmental Research and Risk Assessment(2篇)，Journal of Water Process Engineering(2篇)及《水利学报》《水科学进展》等。14篇曾入选ESI高被引论文，4篇入选ESI热点论文，发明专利4项。近年来发表的第一/通讯的论文如下：
2025年
[1] Tan, Z., Li, H., Zhu, Z., Hou, J., & Wang, Z.* (2025). A water-energy-food-land nexus framework for multi-objective optimization and risk assessment integrating deep reinforcement learning and Copula-based modeling. Water Research, 124474. (Top期刊，IF：12.4，JCR1区)
[2] Tan, Z., Wang, Z.*, Li, H., Song, Q, Ou, Y., & Wu, T. (2025). Balancing water use efficiency and carbon neutrality in mariculture: A multi-objective model for optimizing mariculture structure in China’s coastal provinces. Agricultural Water Management, 109756. (Top期刊，IF：6.5，JCR1区)
[3] Yao, Z., Wang, Z.*, Xu, N., Wu, J., & Cui, X. (2025). Interpretable multi-step ahead prediction of reference evapotranspiration using attention-based ensemble learning method. Journal of Hydrology, 134084. (Top期刊，IF：6.3，JCR1区)
[4] Cheng, L., Wang, Z.*, Pei, R., & Wu, J. (2025). Sustainable urban management and flood resilience in China’s Yangtze river economic belt: Drivers, patterns, and policy synergies. Sustainable Cities and Society, 106737. (Top期刊，IF：12.0，JCR1区)
[5] Zhang, C., Wang, Z.*, Ding, C., & Wu, J. (2025). A robust spatiotemporal prediction model for dissolved oxygen in Eutrophic Lakes using stochastic optimized hybrid deep learning and multi-source data fusion. Journal of Water Process Engineering, 77, 108490. (IF：6.7，JCR1区)
[6] Wang, Z., Ma, C., Tan, Z., & Wu, T. (2025). Low-carbon development pathways for the water-energy-food-carbon nexus in the Yangtze river economic Belt: Insights from coupling coordination and obstacle degree analysis. Journal of Cleaner Production, 523, 146399. (Top期刊，IF：10.0，JCR1区)
[7] Zhang, A., Wang, Z.*, Kang, N., & Wang, P. (2025). GWO-driven adaptive runoff forecasting via hybrid deep learning networks of VMD-RPV and GRU-KAN. Journal of Hydroinformatics, 27(7), 1193-1216. (IF：2.2，JCR2区)
[8] Wang, Z., Ma, C., Wu, J., & Wu, T. (2025). Extreme precipitation risk assessment with improved WOA-Optimized copula model under composite conditions. Theoretical and Applied Climatology, 156(8), 446. (IF：2.7，JCR3区)
[9] Kang, N., Wang, Z.*, Zhang, A., & Chen, H. (2025). Improving the prediction of streamflow in large watersheds based on seasonal trend decomposition and vectorized deep learning models. Ecological Informatics, 90, 103291. (IF：7.3，JCR1区)
[10] Zhu, S., Wang, Z.*, Zhang, W., & Yang, J. (2025). Application of the ResNet-Transformer Model for Runoff Prediction Based on Multi-source Data Fusion. Water Resources Management. 1-20. Doi：10.1007/s11269-025-04241-3. (IF：4.7，JCR1区)
[11] Tan, Z., Li, H., Song, Q., Wang, Z.*, & Cao, Y. (2025). Synergistic Optimization and Interaction Evaluation of Water-Energy-Food-Ecology Nexus under Uncertainty from the Perspective of Urban Agglomeration. Sustainable Cities and Society, 124, 106291. (Top期刊，IF：12.0，JCR1区)
[12] Wang, Z., Zhao, H., Lu, Q., & Wu, T. (2025). Improved non-dominated Sorting Genetic Algorithm III for Efficient of Multi-bjective Cascade Reservoirs Scheduling under Different Hydrological Conditions. Journal of Hydrology, 656, 132998. (Top期刊，IF：6.3，JCR1区)
[13] Li, R., Wang, Z.*, Li, Y., & Wu, T. (2025). Regional ecological risk assessment and transfer mechanism based on improved gravity and social network analysis model: A case study of Northwest China. Ecological Indicators, 172, 113243. (Top期刊，IF：7.3，JCR1区)
[14] Ding, W., Cheng, H., Wang, Z.*, Wu, J., Yang, Q., Zhao, X., Li, Z., Xu, Y., Dong, J., & Yao, Z. (2025). Multimodal Sensor Fusion and Interpretable Deep Learning for Shallow Water Hazardous Geomorphology Features Recognition. IEEE Sensors Journal. 25(7) , pp.11545-11562. (IF：4.5，IEEE系列期)
[15] Wang, Z., Zhu, Z., Luan, H., & Wu, T. (2025). Multi-objective optimal scheduling of cascade reservoirs in complex basin systems: Case study of the Jinsha River-Yalong River confluence basin in China. Journal of Hydrology: Regional Studies, 58, 102240. (IF：5.0)
[16] Wang, B., Wang, Z.*, & Yao, Z. (2025). Enhancing Carbon Price Point-Interval Multi-step-ahead Prediction Using a Hybrid Framework of Autoformer and Extreme Learning Machine with Multi-factors. Expert Systems with Applications, 270, 126467. (Top期刊，ESI高被引，IF：7.5)
[17] Guo, H., Chen, L., Wang, Z.*, & Li, L. (2025). Day-ahead prediction of electric vehicle charging demand based on quadratic decomposition and dual attention mechanisms. Applied Energy, 381, 125198. (Top期刊，IF：11.0)
[18] 黄靖涵, 王兆才*, 吴俊豪, & 姚之远. (2025). 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, 56(2), 240-252.
[19] 丁诚，王兆才*，丁伟杰，程和琴.(2025).基于可解释的多源数据时空特征融合的深度学习集合径流预测.水科学进展，接受.
2024年
[1] Liu, S., Wang, Z.*, & Li, Y. (2024). A novel approach for multivariate time series interval prediction of water quality at wastewater treatment plants. Water Science & Technology, 90(10), 2813-2841. (IF：2.6)
[2] Chu, J., Wang, Z.*, Bao, X., Yao, Z., & Cui, X. (2024). Addressing the contradiction between water supply and demand: a study on multi-objective regional water resources optimization allocation. Environment, Development and Sustainability, 1-29. doi: 10.1007/s10668-024-05214-z (IF：4.7)
[3] 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)
[4] Xie, X., Wang, Z.*, Xu, M., & Xu, N. (2024). Daily PM2.5 concentration prediction based on variational modal decomposition and deep learning for multi‑site temporal and spatial fusion of meteorological factors. Environmental Monitoring and Assessment, 196, 859. (IF：2.9)
[5] 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，ESI高被引，IF：8.0)
[6] 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：10.0)
[7] 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)
[8] 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. (ESI高被引，IF：4.6)
[9] 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：6.3)
[10] 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：4.4，IEEE Trans)
[11] 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：8.4)
[12] 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，ESI高被引，IF：7.3)
[13] 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)
[14] 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. (ESI高被引，IF：4.6)
[15] 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. (ESI高被引，IF：4.7)
[16] 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)
[17] 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，ESI高被引，IF：6.3)
2023年
[1] 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)
[2] Zhang, C., Zou, Z., Wang, Z.*, & Wang, J. (2024). Ensemble deep learning modeling for Chlorophyll-a concentration prediction based on two-layer decomposition and attention mechanisms. Acta Geophysica, 72(5), 3447-3471. (IF：2)
[3] 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)
[4] 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)
[5] 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：4.4，IEEE Trans系列)
[6] 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，ESI高被引，IF：5.9)
[7] 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)
[8] 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)
[9] 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. (ESI高被引，IF：6.4)
[10] 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)
[11] 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)
[12] 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: Regional Studies, 47, 101435. (IF：5.0)
[13] 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，ESI高被引，IF：10.2)
[14] 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)
[15] 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. (ESI高被引，IF：4.7)
[16] 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：7.3)
科研项目：
近年来主持省部级以上科研项目十余项，包括：
（1）上海市科学技术委员会软科学研究项目，数字孪生赋能的上海近海复合灾害链风险治理研究——多尺度动态韧性与协同防控机制设计，2025/5-2026/4，主持；
（2）中国国家统计局全国统计科学研究项目，基于多源数据融合的统计与人工智能模型在水质突变风险监测预警中的应用研究，2025/9-2026/12，主持；
（3）中国水利水电科学研究院内蒙古阴山北麓草原生态水文国家野外科学观测研究站开放研究基金，基于多源数据融合的AI驱动无资料地区洪水预报预警研究，2025/7-2027/6，主持；
（4）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；
（5）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；
（6）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；
（7）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；
（8）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。
（9）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：
《Applied Computational Intelligence and Soft Computing》期刊编辑，《Water》，《Scientific Reports》特刊编辑，以及《Water》，《River》，《南水北调与水利科技》，《重庆大学学报》，《华北水利水电大学学报》，《地域研究与开发》期刊青年编委。