Donghwan Kim Defends Ph.D. Dissertation

Donghwan Kim Defends Ph.D. Dissertation

River Discharge Estimates Improved Using Ensemble Learning

Ph.D. candidate Donghwan Kim successfully defended his dissertation titled, "Ensemble Learning Regression for Estimating River Discharge Using Remotely Sensed Data and Hydrological Model." A new approach to estimating river discharge using ensemble learning regression (ELQ) was developed. Ensemble learning designates a series of procedures to train several functions and combine their results based on an integrating rule. ELQ generates more accurate estimates of river discharge compared to those obtained from traditional empirical methods. Efforts were also made to improve the accuracy of estimates of discharge for poorly gauged rivers using remotely sensed data, hydrologic models, and ELQ.

Donghwan's Geosensing Systems Engineering & Sciences (GSES) advisor was Dr. Hyongki Lee. Congratulations, Donghwan!

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