
【个人简介】
张茜茜,女,副教授,硕士生导师,中共党员,博士学位。先后分别于华东理工大学、中国科学院大学和加拿大麦克马斯特大学(2021泰晤士世界大学排名第69)获学士、硕士和博士学位。主要从事环境管理、环境模型、不确定性分析、经济统计与分析等方向的研究。现任成都信息工程大学讲师,兼任Environments和Hydrology特邀编辑,以及Journal of Hydrology、Journal of Contaminant Hydrology及Journal of Ambient Intelligence and Humanized Computing等国际期刊的审稿人。
【研究方向】
1.环境管理模型及系统优化
2.不确定性分析及风险管理
3.大数据分析及机器学习
4.旅游管理及数据分析
5.经济统计与分析
【在研项目】
1.不确定性下复杂系统模拟优化管理模型研究,成都信息工程大学,主持,2023-2024年
2.成都房地产业在经济中的地位与作用研究,成都市统计局,主持,2023年
3.新疆人口发展趋势研究,新疆维吾尔自治区统计局,主持,2023年
4.文化旅游产业综合贡献度研究服务采购项目,雅安市文化体育和旅游局,主持,2023年
【完成项目】
1.Real-time Prediction of Chloride Concentration in River Water Based on Continuous Sensors and Machine Learning, MacDATA Institute, McMaster University,主持,2020-2021
2.新津区第七次全国人口普查资料开发应用采购项目,新津区统计局,主持,2021年
3.青羊区总部经济发展研究,青羊区统计局,主持,2020年
4.新津县经济高质量发展研究,新津县统计局,主持,2019年
5.2018年四川省季(年)度财政收入预测,四川省统计局,主持,2018年
【学术专著】
1.低收入群体向中等收入阶层跃迁问题探索:基于收入流动性视角,山西经济出版社,2023年
【发表论文】
1.Zhang, Q.Q., Zhang, F., Erfani, T., & Zhu, L. (2023). Bagged stepwise cluster analysis for probabilistic river flow prediction.J. Hydrol., 625, 129995.(SCI中科院一区,第一作者)
2.Zhang, Q.Q., Li, Z., Zhu, L., Zhang, F., Sekerinski, E., Han, J.C., & Zhou, Y. (2021). Real-time prediction of river chloride concentration using ensemble learning.Enviro. Pollu., 118116.(SCI中科院一区,第一作者)
3.Zhang, Q.Q.& Li, Z. (2021). Data-driven interval credibility constrained quadratic programming model for water quality management under uncertainty.J. Environ. Manage., 293, 11279.(SCI中科院二区,第一作者)
4.Zhang, Q.Q., Li, Z., & Huang, W. (2021). Simulation-based interval chance-constrained quadratic programming model for water quality management: A case study of the central Grand River in Ontario, Canada.Enviro. Res., 110206.(SCI中科院二区,第一作者)
5.Zhang, Q.Q.& Li, Z. (2020). Development of an interval quadratic programming water quality management model and its solution algorithms.J. Clean. Prod., 119319.(SCI中科院一区,第一作者)
6.Zhang, Q.Q., Li, Z., Snowling, S., Siam, A., & El-Dakhakhni, W. (2019). Predictive models for wastewater flow forecasting based on time series analysis and artificial neural network.Water Sci. Technol., 80(2), 243-253.(SCI中科院四区,第一作者)
7.Zhang, Q.Q., Jin, Z.D., Zhang, F., & Xiao, J. (2015). Seasonal variation in river water chemistry of the middle reaches of the Yellow River and its controlling factors.J. Geochem. Explor., 156, 101-113.(SCI中科院二区,第一作者)
8.Zhang, B.L., Ouyang, C.J., et al.,Zhang,Q.Q.(2024).Deep Learning for Cross-Region Streamflow and Flood Forecasting at a Global Scale.The Innovation, 5(3), 100617.(SCI中科院一区)
9.Zhou, P.X., Li, Z., Snowling, S., Goel, R., &Zhang, Q.Q.(2022).Multi-step ahead prediction of hourly influent characteristics for wastewater treatment plants: a case study from North America.Environ. Monit. Assess.,194(5), 1-14.(SCI中科院四区)
10.Li, C.C., Cai, Y.P., Li, Z.,Zhang, Q.Q., Sun, L., Li, X.Y., & Zhou, P.X. (2021).Hydrological response to climate and land use changes in the dry-warm valley of the Upper Yangtze River.Engineering.(SCI中科院一区)
11.Boyd, G., Na, D., Li, Z., Snowling, S.,Zhang,Q.Q., & Zhou, P.X. (2019).Influent forecasting for wastewater treatment plants in North America.Sustainability, 11 (6), 1764.(SCI中科院三区)
12.Zhou, P.X., Li, Z., Snowling, S., Goel, R., &Zhang,Q.Q.(2019).Short-Term Wastewater influent prediction based on random forests and multi-layer perceptron.J. Environ. Inform. Letters,1(2), 87-93.(EI)
13.Li, X.Y., Li, Z.,Zhang,Q.Q., Zhou, P.X., & Huang. W. (2019).Prediction of long-term near-surface temperature based on NA-CORDEX output.J. Environ. Inform. Letters,2(1), 10-18.(EI)
14.Zhang, W., Lin, K.F., Zhou, J., Zhang, W., Liu, L.L., &Zhang,Q.Q.(2014).Cadmium accumulation, sub-cellular distribution and chemical forms in rice seedling in the presence of sulfur.Environ. Toxicol. Phar., 37(1), 348-353.(SCI中科院三区)
15.Li, Z., Li, X., Zhou, P.,Zhang, Q.Q., Li, C., & Cai, Y. (2022). Climate downscaling and hydrological impact assessment based on long short-term memory neural networks.In18th Annual Meeting of the Asia Oceania Geosciences Society: Proceedings of the 18th Annual Meeting of the Asia Oceania Geosciences Society (AOGS 2021)(pp. 115-116).(国际会议论文)
【联系方式】
电子邮件:zqq@cuit.edu.cn