Xiaogang Gao
Affiliations: | Civil Engineering - Ph.D. | University of California, Irvine, Irvine, CA |
Area:
Civil EngineeringGoogle:
"Xiaogang Gao"
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Publications
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| Tao Y, Hsu K, Ihler A, et al. (2018) A Two-Stage Deep Neural Network Framework for Precipitation Estimation from Bispectral Satellite Information Journal of Hydrometeorology. 19: 393-408 |
| Nguyen P, Thorstensen A, Sorooshian S, et al. (2017) Evaluation of CMIP5 Model Precipitation Using PERSIANN-CDR Journal of Hydrometeorology. 18: 2313-2330 |
| Tao Y, Gao X, Ihler A, et al. (2017) Precipitation Identification with Bispectral Satellite Information Using Deep Learning Approaches Journal of Hydrometeorology. 18: 1271-1283 |
| Yang T, Asanjan AA, Welles E, et al. (2017) Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information Water Resources Research. 53: 2786-2812 |
| Tao Y, Gao X, Hsu K, et al. (2016) A deep neural network modeling framework to reduce bias in satellite precipitation products Journal of Hydrometeorology. 17: 931-945 |
| Yang T, Gao X, Sorooshian S, et al. (2016) Simulating California reservoir operation using the classification and regression-tree algorithm combined with a shuffled cross-validation scheme Water Resources Research. 52: 1626-1651 |
| Liu H, Sorooshian S, Gao X. (2015) Assessment of the spatial and seasonal variation of the error-intensity relationship in satellite-based precipitation measurements using an adaptive parametric model Journal of Hydrometeorology. 16: 1700-1716 |
| Yang T, Gao X, Sellars SL, et al. (2015) Improving the multi-objective evolutionary optimization algorithm for hydropower reservoir operations in the California Oroville-Thermalito complex Environmental Modelling and Software. 69: 262-279 |
| Chu W, Yang T, Gao X. (2014) Comment on “High-dimensional posterior exploration of hydrologic models using multiple-try DREAM (ZS) and high-performance computing” by Eric Laloy and Jasper A. Vrugt Water Resources Research. 50: 2775-2780 |
| Sellars S, Nguyen P, Chu W, et al. (2013) Computational Earth Science: Big Data Transformed Into Insight Eos, Transactions American Geophysical Union. 94: 277-278 |