An embedded system is a modular micro-computer with a dedicated function. It can assess on-site condition and proide timely disaster prevention and mitigation without human interference.
Numerical modeling has been a useful tool for practical applications and analysis such as the development of early warning system and human behavior preciction.
Physical and software components are deeply intertwined in cyber-physical systems, each operating on different spatial and temporal scales, and interacting with each other that change with context.
Cyber-Physical System
Numerical Modeling
Embedded System
Numerical Modeling
Numerical Modeling
Numerical Modeling
Josh started his new job in National Chiao Tung University. Hao-Ming, Chia-Wei, and Szu-Hao were the first three members of the team.
The lab name "THINKLAB" has officially confirmed. The core values of the lab are echnology . Hydrology . Integration . Need . Knowledge. Major focus is disater prevention and mitigation. Obaja from Indonesia and Hong-Ming joined the lab as the first phd student and a post-doctoral researcher at the same time. Kevin and Allen started their independent stuies with the lab during the same time.
The lab started its first edge-computing device and associated experiment. Welocme two graduate students, Tina and Allen, joined the lab.
We are always looking forward to working with you anytime in the future.
Assistant Professor
Graduate Student
Research Assistant
Postdoctoral Researcher
Graduate Student
Graduate Student
Graduate Student
Graduate Student
Let us know if you are insterested in working with us.
Year 2020
Year 2019
Year 2019
Wijaya, O. T. & Yang, T. H. (2020). A novel hybrid approach based on cellular automata and digital elevation model for rapid flood assessment. Journal of Hydrology, Under review.
Yang, S. C., Yang, T. H., Chang, Y. C., Chen, C. H., Lin, M. Y., Ho, J. Y., & Lee, K. T. (2020). Development of a hydrological ensemble prediction system to help decision-making for floods during typhoon events. Sustainability 2020, 12(10), 4258.
Yang, T. H., & Liu, W. C. (2020). A general overview of the risk-reduction strategies for floods and droughts. Sustainability 2020, 12(7), 2687.
Yang, T. H., Wang, C. W., & Lin, S. J. (2020). ECOMSNet – An edge computing-based sensory network for real-time water level prediction and correction. Environmental Modelling & Software, 131, September 2020, 104771.
Yang, T. H., & Tsai, C. C. (2019). Using numerical weather model outputs to forecast wind gusts during typhoons. Journal of Wind Engineering and Industrial Aerodynamics, 188, 247-259.
Lee, K. T., Ho, J. Y., Kao, H. M., Lin, G. F., & Yang, T. H. (2019). Using ensemble precipitation forecasts and a rainfall-runoff model for hourly reservoir inflow forecasting during typhoon periods. Journal of Hydro-environment Research, 22, 29-37.
Wu, M. C., Yang, S. C., Yang, T. H., & Kao, H. M. (2018). Typhoon Rainfall Forecasting by Means of Ensemble Numerical Weather Predictions with a GA-Based Integration Strategy. Atmosphere, 9(11), 425.
Yang, T. H., Yang, S. C., Kao, H. M., Wu, M. C., & Hsu, H. M. (2018). Cyber-physical-system-based smart water system to prevent flood hazards. Smart Water, 3(1), 1.
Yang, T. H., Hwang, G. D., & Huang, X. M. (2018). Combining Numerical Rainfall Forecasts and Realtime Observations to Improve Early Inundation Warnings. In Advances in Hydroinformatics (pp. 515-524). Springer, Singapore.
Yang, T. H., Hwang, G. D., Tsai, C. C., & Ho, J. Y. (2016). Using rainfall thresholds and ensemble precipitation forecasts to issue and improve urban inundation alerts. Hydrology and Earth System Sciences, 20(12), 4731-4745.
Yang, T. H., Feng, L., & Chang, L. Y. (2016). Improving radar estimates of rainfall using an input subset of artificial neural networks. Journal of Applied Remote Sensing, 10(2), 026013.
Yang, T. H., Chen, Y. C., Chang, Y. C., Yang, S. C., & Ho, J. Y. (2015). Comparison of different grid cell ordering approaches in a simplified inundation model. Water, 7(2), 438-454.
Yang, T. H., Yang, S. C., Ho, J. Y., Lin, G. F., Hwang, G. D., & Lee, C. S. (2015). Flash flood warnings using the ensemble precipitation forecasting technique: A case study on forecasting floods in Taiwan caused by typhoons. Journal of Hydrology, 520, 367-378.
Yang, T. H., Chen, Y. C., Chang, Y. C., Yang, S. C., & Ho, J. Y. (2015). Comparison of different grid cell ordering approaches in a simplified inundation model. Water, 7(2), 438-454.
Yang, S. C., & Yang, T. H. (2014). Uncertainty assessment: reservoir inflow forecasting with ensemble precipitation forecasts and HEC-HMS. Advances in Meteorology, 2014.
Yang, T. H., Ho, J. Y., Hwang, G. D., & Lin, G. F. (2014). An indirect approach for discharge estimation: A combination among micro-genetic algorithm, hydraulic model, and in situ measurement. Flow Measurement and Instrumentation, 39, 46-53.
Yang, T. H., Wang, Y. C., Tsung, S. C., & Guo, W. D. (2014). Applying micro-genetic algorithm in the one-dimensional unsteady hydraulic model for parameter optimization. Journal of Hydroinformatics, 16(4), 772-783.
Younis, B. A., & Yang, T. H. (2011). Prediction of the effects of vortex shedding on UV disinfection efficiency. Journal of Water Supply: Research and Technology-Aqua, 60(3), 147-158.
Younis, B. A., & Yang, T. H. (2010). Computational modeling of ultraviolet disinfection. Water Science and Technology, 62(8), 1872-1878.
Wijaya, O. T. & Yang, T. H. (2020, September). Developing a Cellular Automata-based Inundation Model for rapid flood response in an urban and low-lying area. In Proc. Int. Conf. 2020 IAHR-APD, Saporo, Japan.
Yang, T. H., Hsu, H. M., & Kao, H. M. (2019, June). Integrations of an early warning system and business continuity plan for disaster management in a science park. In Proc. Int. Conf. SimHydro 2019: Choosing the right model in applied hydraulics. SHF.
Tsai, C. C., Yang, T. H., Hsiao, L. F., Wang, C. J., Chang, L. Y., Chiang, C. C., ... & Hunag, C. Y. (2018, April). Typhoon wind gust product for high speed rail system in Taiwan. In EGU General Assembly Conference Abstracts (Vol. 20, p. 12351).
